Smart City test bed
TEAM
| Name | Position | Department |
|---|---|---|
| Bharadwaj Amrutur (Principal Investigator) | Chairman Professor | Robert Bosch Centre for Cyber-Physical Systems Electrical Communication Engineering |
| Yogesh Simmhan | Assistant Professor | Computational and Data Sciences |
| Rajesh Sundaresan | Professor | Robert Bosch Centre for Cyber-Physical Systems Electrical Communication Engineering |
| Malati Hegde | Principal Scientific Officer | Electrical Communication Engineering |
Abstract
The Indian Government has identified Smart Cities as a priority area for development in the coming years. ICT will play a key role in supporting smart city solutions and more specifically, IoT technologies will be a key enabler for providing the “smarts”. The requirements from citizens in cities is diverse and cuts across many different verticals like transportation, water management, solid waste management, smart parking etc. Typically, each vertical will be addressed by a different vendor, who will provide an end-to-end solution. However it has been recognized of late, that a better approach might be to have a horizontal approach where in sensors, and other data are made available across different silos – in order to foster new, cost effective solutions to various city related problems and citizen needs. A simple example is that of a camera sensor which can aid in not only in surveillance but also in crowd management, smart parking, transit operations management etc. applications. Hence there is a need to develop smart city ICT/IoT framework as a generic platform that will support a diverse set of applications.
The main thrust of this work will be to develop an instrumented test bed in the IISc campus, which will consist of a collection of sensors, gateways, middleware and server side software, supporting a few candidate applications of energy monitoring, water monitoring and solid waste management. The testbed will be a hybrid of real and virtual components. Being able to support such a hybrid system will enable us to test concepts at scales of real cities with 1000s of gateways and 10s of thousands of sensors, while the real world portion of the testbed will still be small and low cost. The scaling limits will be determined via analysis of current and future requirements for Indian Smart Cities in terms of:
- Data base size, query latency, IO/second, availability
- Communication throughput, latency, loss tolerance
- Gateway performance (throughput), memory, storage,
- Sensor density per square kilometer and its data bandwidth
Finally the test bed will be validated via the physical portions instantiated in the IISc campus as well as the virtual portions instantiated to mimic a city of the scale of Bangalore. The concept of using light poles as smart city infrastructures will also be incorporated in the test bed via instrumenting about 10 light poles on the campus, with the gateways and sensors.
The aim of the test bed will be two-fold:
Allow for experimentation of different technologies at each level of the smart city solutions like:
- Different sensor hardware and firmware stacks, including crowd sourced sensing
- Different wireless front-haul schemes like WiFi, BLE, Sub-GHz
- Different gateway hardware and software stacks to support distributed analytics
- Different edge and cloud computing architectures
- Different data persistence platforms including in-memory DB, time-series DB, and NoSQL
- Different realtime and batch analytics platforms
Support for metrics at various levels from the sensors to the server, both in hardware and software to enable a quantitative assessment of the performance of various alternative approaches.
We believe that this activity will open up opportunities to explore new concepts like gateway virtualization, virtual agents, dynamic resource management, etc. in the second year onwards.
Project Publications
| 1. | Rakshit Ramesh; Mukunth Arunachalam; Hari Krishna Atluri; Chetan Kumar; SVR Anand; Paventhan Arumugam; Bharadwaj, Amrutur LoRaWAN for smart cities: experimental study in a campus deployment, Book Chapter in for IoT, Book Chapter LPWAN Technologies; Applications, M2M (Ed.): pp. 327-345, Academic Press, 2020. @inbook{@Rakshit, title = {LoRaWAN for smart cities: experimental study in a campus deployment,}, author = {Rakshit Ramesh; Mukunth Arunachalam; Hari Krishna Atluri; Chetan Kumar; SVR Anand; Paventhan Arumugam; Bharadwaj, Amrutur}, editor = {Book Chapter in LPWAN Technologies for IoT and M2M Applications}, url = {https://cps.iisc.ac.in/wp-content/uploads/2020/10/LoRaWAN-for-Smart-Cities-Experimental-Study-in-a-Campus-Deployment.pdf}, doi = {10.1016/B978-0-12-818880-4.00016-8}, year = {2020}, date = {2020-08-01}, pages = {327-345}, publisher = {Academic Press}, abstract = {The advent of cheap low-powered long-range radio technologies such as LoRa that operate on an unlicensed band resulted in many real-world deployments of smart city applications. Unlike a rural and semiurban areas where we can expect long radio-frequency (RF) propagation due to strong line-of-sight component, a city that typically comprises diverse terrain environments comprising a mix of buildings, dense wooded areas, parks, and gated communities limits the radio coverage and range. This necessitates the need for proper RF network planning to ensure optimal coverage of the network in such areas with the ability to remotely manage the infrastructure equipment to make deployment and network management hassle-free. On a city scale, there is a need for an interoperable middleware that provides a single point of contact for a developer to operate devices on various network protocols such as LoRa and Zigbee. In this chapter, we describe our experiences in deploying such an interoperable long-range wide-area network and management aspects of it in a campus environment with dense foliage interspersed with buildings and shed light on some deployment insights we have obtained in order to make an optimal network deployment.}, keywords = {}, pubstate = {published}, tppubtype = {inbook} } The advent of cheap low-powered long-range radio technologies such as LoRa that operate on an unlicensed band resulted in many real-world deployments of smart city applications. Unlike a rural and semiurban areas where we can expect long radio-frequency (RF) propagation due to strong line-of-sight component, a city that typically comprises diverse terrain environments comprising a mix of buildings, dense wooded areas, parks, and gated communities limits the radio coverage and range. This necessitates the need for proper RF network planning to ensure optimal coverage of the network in such areas with the ability to remotely manage the infrastructure equipment to make deployment and network management hassle-free. On a city scale, there is a need for an interoperable middleware that provides a single point of contact for a developer to operate devices on various network protocols such as LoRa and Zigbee. In this chapter, we describe our experiences in deploying such an interoperable long-range wide-area network and management aspects of it in a campus environment with dense foliage interspersed with buildings and shed light on some deployment insights we have obtained in order to make an optimal network deployment. |
| 2. | Karanjkar, Neha; Tejasvi, Poorna Chandra; Amrutur, Bharadwaj A simpy-based simulation testbed Presentation 18.04.2019. @misc{Karanjkar2019, title = {A simpy-based simulation testbed }, author = {Neha Karanjkar and Poorna Chandra Tejasvi and Bharadwaj Amrutur}, doi = {10.1145/3302505.3312591}, year = {2019}, date = {2019-04-18}, abstract = {A real-time testbed that emulates a large number of IoT end-points generating traffic to the middleware/application layers can be used for debugging and performance evaluation of the smart-city software platforms prior to deployment. We propose an architecture for such a simulation testbed based on Python's SimPy library. The simulated IoT end-points communicate with the middleware in real-time and can also interact directly with each other and with a common shared environment. This makes the testbed particularly suited for modeling system-wide scenarios such as synchronized faults and power outages.}, keywords = {}, pubstate = {published}, tppubtype = {presentation} } A real-time testbed that emulates a large number of IoT end-points generating traffic to the middleware/application layers can be used for debugging and performance evaluation of the smart-city software platforms prior to deployment. We propose an architecture for such a simulation testbed based on Python's SimPy library. The simulated IoT end-points communicate with the middleware in real-time and can also interact directly with each other and with a common shared environment. This makes the testbed particularly suited for modeling system-wide scenarios such as synchronized faults and power outages. |
| 3. | Babu, Arun; Thomas, Jithin Jose Freestyle, a randomized version of ChaCha for resisting offline brute-force and dictionary attacks Journal Article Forthcoming Journal of Information Security and Applications, 49 , Forthcoming. @article{Babu2019, title = {Freestyle, a randomized version of ChaCha for resisting offline brute-force and dictionary attacks}, author = {Arun Babu and Jithin Jose Thomas}, url = {http://10.0.54.4/wp-content/uploads/2019/10/Freestyle-a-randomized-version-of-ChaCha-for-resisting-offline-brute-force-and-dictionary-attacks.pdf}, doi = {10.1016/j.jisa.2019.102396}, year = {2019}, date = {2019-12-01}, journal = {Journal of Information Security and Applications}, volume = {49}, abstract = {This paper introduces Freestyle, a randomized and variable round version of the ChaCha cipher. Freestyle uses the concept of hash based halting condition where a decryption attempt with an incorrect key is likely to take longer time to halt. This makes Freestyle resistant to key-guessing attacks i.e. brute-force and dictionary based attacks. Freestyle demonstrates a novel approach for ciphertext randomization by using random number of rounds for each block, where the exact number of rounds are unknown to the receiver in advance. Freestyle provides the possibility of generating 2^128 different ciphertexts for a given key, nonce, and message; thus resisting key and nonce reuse attacks. Due to its inherent random behavior, Freestyle makes cryptanalysis through known-plaintext, chosen-plaintext, and chosen-ciphertext attacks difficult in practice. On the other hand, Freestyle has costlier cipher initialization process, typically generates 3.125% larger ciphertext, and was found to be 1.6 to 3.2 times slower than ChaCha20. Freestyle is suitable for applications that favor ciphertext randomization and resistance to key-guessing and key reuse attacks over performance and ciphertext size. Freestyle is ideal for applications where ciphertext can be assumed to be in full control of an adversary, and an offline key-guessing attack can be carried out. }, keywords = {}, pubstate = {forthcoming}, tppubtype = {article} } This paper introduces Freestyle, a randomized and variable round version of the ChaCha cipher. Freestyle uses the concept of hash based halting condition where a decryption attempt with an incorrect key is likely to take longer time to halt. This makes Freestyle resistant to key-guessing attacks i.e. brute-force and dictionary based attacks. Freestyle demonstrates a novel approach for ciphertext randomization by using random number of rounds for each block, where the exact number of rounds are unknown to the receiver in advance. Freestyle provides the possibility of generating 2^128 different ciphertexts for a given key, nonce, and message; thus resisting key and nonce reuse attacks. Due to its inherent random behavior, Freestyle makes cryptanalysis through known-plaintext, chosen-plaintext, and chosen-ciphertext attacks difficult in practice. On the other hand, Freestyle has costlier cipher initialization process, typically generates 3.125% larger ciphertext, and was found to be 1.6 to 3.2 times slower than ChaCha20. Freestyle is suitable for applications that favor ciphertext randomization and resistance to key-guessing and key reuse attacks over performance and ciphertext size. Freestyle is ideal for applications where ciphertext can be assumed to be in full control of an adversary, and an offline key-guessing attack can be carried out. |
| 4. | Poorna Chandra, Tejasvi User story contest @ RabbitMQ Summit Presentation 04.11.2019. @misc{@Poorna2019, title = {User story contest @ RabbitMQ Summit}, author = {Poorna Chandra, Tejasvi }, year = {2019}, date = {2019-11-04}, abstract = {RabbitMQ Summit brings together users and developers from around the world. Learn from speakers and keynotes on what’s happening in and around RabbitMQ, and how top companies utilise RabbitMQ to power their services. }, keywords = {}, pubstate = {published}, tppubtype = {presentation} } RabbitMQ Summit brings together users and developers from around the world. Learn from speakers and keynotes on what’s happening in and around RabbitMQ, and how top companies utilise RabbitMQ to power their services. |
| 5. | Ghosh, Rajrup; Simmhan, Yogesh Distributed scheduling of event analytics across edge and cloud Journal Article ACM Transactions on Cyber-Physical Systems, 2 (4), pp. 24:1-28, 2018. @article{Ghosh2018, title = {Distributed scheduling of event analytics across edge and cloud}, author = {Rajrup Ghosh and Yogesh Simmhan}, url = {http://www.rbccps.org/wp-content/uploads/2018/12/a24-ghosh.pdf}, doi = {10.1145/3140256}, year = {2018}, date = {2018-10-31}, journal = {ACM Transactions on Cyber-Physical Systems}, volume = {2}, number = {4}, pages = {24:1-28}, abstract = {Internet of Things (IoT) domains generate large volumes of high-velocity event streams from sensors, which need to be analyzed with low latency to drive decisions. Complex Event Processing (CEP) is a Big Data technique to enable such analytics and is traditionally performed on Cloud Virtual Machines (VM). Leveraging captive IoT edge resources in combination with Cloud VMs can offer better performance, flexibility, and monetary costs for CEP. Here, we formulate an optimization problem for energy-aware placement of CEP queries, composed as an analytics dataflow, across a collection of edge and Cloud resources, with the goal of minimizing the end-to-end latency for the dataflow. We propose a Genetic Algorithm (GA) meta-heuristic to solve this problem and compare it against a brute-force optimal algorithm (BF). We perform detailed real-world benchmarks on the compute, network, and energy capacity of edge and Cloud resources. These results are used to define a realistic and comprehensive simulation study that validates the BF and GA solutions for 45 diverse CEP dataflows, LAN and WAN setup, and different edge resource availability. We compare the GA and BF solutions against random and Cloud-only baselines for different configurations for a total of 1,764 simulation runs. Our study shows that GA is within 97% of the optimal BF solution that takes hours, maps dataflows with 4--50 queries in 1--26s, and only fails to offer a feasible solution ≤20% of the time.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Internet of Things (IoT) domains generate large volumes of high-velocity event streams from sensors, which need to be analyzed with low latency to drive decisions. Complex Event Processing (CEP) is a Big Data technique to enable such analytics and is traditionally performed on Cloud Virtual Machines (VM). Leveraging captive IoT edge resources in combination with Cloud VMs can offer better performance, flexibility, and monetary costs for CEP. Here, we formulate an optimization problem for energy-aware placement of CEP queries, composed as an analytics dataflow, across a collection of edge and Cloud resources, with the goal of minimizing the end-to-end latency for the dataflow. We propose a Genetic Algorithm (GA) meta-heuristic to solve this problem and compare it against a brute-force optimal algorithm (BF). We perform detailed real-world benchmarks on the compute, network, and energy capacity of edge and Cloud resources. These results are used to define a realistic and comprehensive simulation study that validates the BF and GA solutions for 45 diverse CEP dataflows, LAN and WAN setup, and different edge resource availability. We compare the GA and BF solutions against random and Cloud-only baselines for different configurations for a total of 1,764 simulation runs. Our study shows that GA is within 97% of the optimal BF solution that takes hours, maps dataflows with 4--50 queries in 1--26s, and only fails to offer a feasible solution ≤20% of the time. |
| 6. | Amrutur, Bharadwaj; Darbari, Hemant Final report on the project "Study of India appropriate technology (IoT) solutions for Smart Cities" Technical Report 2018. @techreport{Amrutur2018, title = {Final report on the project "Study of India appropriate technology (IoT) solutions for Smart Cities"}, author = {Bharadwaj Amrutur and Hemant Darbari}, url = {http://www.rbccps.org/wp-content/uploads/2018/10/IISc_IoT4SmartCities_Consolidated_Report.pdf}, year = {2018}, date = {2018-04-30}, abstract = {The main objectives of our project are: (1) Recommendation and guidelines for Smart City RFPs related to IoT specific technologies, driven by India specific use case analysis and emerging technology adoption methodology, and (2) India appropriate reference architecture for IoT enabled Smart cities through a collaborative platform of domain experts from industry, academia, government, start-ups, professional bodies and user agencies. We conducted two workshops with City administrators: One in Chandigarh and another in Electronics City, to understand the city’s requirements. A series of telecons/webcons were held with technical presentations from a diverse set of domain experts from industry, academia, government, startups, etc. Further deliberations and discussions were done to synthesize the view points in this report.}, keywords = {}, pubstate = {published}, tppubtype = {techreport} } The main objectives of our project are: (1) Recommendation and guidelines for Smart City RFPs related to IoT specific technologies, driven by India specific use case analysis and emerging technology adoption methodology, and (2) India appropriate reference architecture for IoT enabled Smart cities through a collaborative platform of domain experts from industry, academia, government, start-ups, professional bodies and user agencies. We conducted two workshops with City administrators: One in Chandigarh and another in Electronics City, to understand the city’s requirements. A series of telecons/webcons were held with technical presentations from a diverse set of domain experts from industry, academia, government, startups, etc. Further deliberations and discussions were done to synthesize the view points in this report. |
| 7. | Ramesh, Rakshit; Acharya, Srikrishna; Rajaraman, Vasanth; Babu, Arun; Joglekar, Ashish; Sharma, Abhay; Amrutur, Bharadwaj; Namekar, Prashant Interoperable middleware for smartcities - Streetlighting on LoRaWAN as a case study Presentation 07.01.2018. @misc{Ramesh2018, title = {Interoperable middleware for smartcities - Streetlighting on LoRaWAN as a case study}, author = {Rakshit Ramesh and Srikrishna Acharya and Vasanth Rajaraman and Arun Babu and Ashish Joglekar and Abhay Sharma and Bharadwaj Amrutur and Prashant Namekar}, url = {http://www.rbccps.org/wp-content/uploads/2018/08/AnInteroperableMiddleware.pdf}, year = {2018}, date = {2018-01-07}, booktitle = {10th International Conference on Communication Systems and Networks (COMSNETS), 03.-07.01.18, Bangalore}, abstract = {A smart city, is like every other organism a structured and organized entity. An organism comprises of a brain that performs its tasks via its appendages, just as smart cities should. However the brain needs a spine through which it communicates information to its appendages, becomes a point of confluence of different sensory and actuator pathways and facilitates activities. We herein put forth our work involving the building of such a spine for a smart city, and focus on the last mile communication aspects, especially using an LPWAN network and an implementation example with smart streetlights.}, keywords = {}, pubstate = {published}, tppubtype = {presentation} } A smart city, is like every other organism a structured and organized entity. An organism comprises of a brain that performs its tasks via its appendages, just as smart cities should. However the brain needs a spine through which it communicates information to its appendages, becomes a point of confluence of different sensory and actuator pathways and facilitates activities. We herein put forth our work involving the building of such a spine for a smart city, and focus on the last mile communication aspects, especially using an LPWAN network and an implementation example with smart streetlights. |
| 8. | Joglekar, Ashish; Hegde, Balachandra Online I-V Tracer for per string monitoring and maintenance of PV panels Conference Proceedings of the 44th Annual Conference of the IEEE Industrial Electronics Society (IECON), 21.-23.10.18, Washington, D.C. (USA), 2018. @conference{Joglekar2018b, title = {Online I-V Tracer for per string monitoring and maintenance of PV panels}, author = {Ashish Joglekar and Balachandra Hegde}, url = {http://www.rbccps.org/wp-content/uploads/2019/05/08591616.pdf}, doi = {10.1109/IECON.2018.8591616}, year = {2018}, date = {2018-12-31}, booktitle = {Proceedings of the 44th Annual Conference of the IEEE Industrial Electronics Society (IECON), 21.-23.10.18, Washington, D.C. (USA)}, pages = {1890-1894}, abstract = {Large scale solar photovoltaic plants need to be monitored regularly for determining location and type of fault, cleaning schedules, operating point and performance. We propose a circuit that sits at the junction box level to provide `on demand', `online' I-V traces for series connected panels. This sparse sensing approach works on a per string basis and is therefore economical. The proposed online I-V tracer topology does not require the plant to be brought offline to obtain the I-V trace. The load's power requirement is met during the trace. The shape of the I-V trace helps determine the type of fault and localizes the fault to a specific string. The proposed solution has been tested in a practical field deployment. An analytics engine is also being developed to use the recorded I-V curve to provide optimal cleaning schedules, fault diagnosis and maintenance alerts.}, keywords = {}, pubstate = {published}, tppubtype = {conference} } Large scale solar photovoltaic plants need to be monitored regularly for determining location and type of fault, cleaning schedules, operating point and performance. We propose a circuit that sits at the junction box level to provide `on demand', `online' I-V traces for series connected panels. This sparse sensing approach works on a per string basis and is therefore economical. The proposed online I-V tracer topology does not require the plant to be brought offline to obtain the I-V trace. The load's power requirement is met during the trace. The shape of the I-V trace helps determine the type of fault and localizes the fault to a specific string. The proposed solution has been tested in a practical field deployment. An analytics engine is also being developed to use the recorded I-V curve to provide optimal cleaning schedules, fault diagnosis and maintenance alerts. |
| 9. | Simmhan, Yogesh; Ravindra, Pushkara; Chaturvedi, Shilpa; Hedge, Malati; Ballamajalu, Rashmi Towards a data‐driven IoT software architecture for Smart City utilities Journal Article Software: Practice and Experience, 48 (7), pp. 1390-1416, 2018. @article{Simmhan2018, title = {Towards a data‐driven IoT software architecture for Smart City utilities}, author = {Yogesh Simmhan and Pushkara Ravindra and Shilpa Chaturvedi and Malati Hedge and Rashmi Ballamajalu}, url = {http://www.rbccps.org/wp-content/uploads/2018/12/Simmhan_et_al-2018-Software3A_Practice_and_Experience.pdf}, doi = {10.1002/spe.2580}, year = {2018}, date = {2018-07-31}, journal = {Software: Practice and Experience}, volume = {48}, number = {7}, pages = {1390-1416}, abstract = {The Internet of things (IoT) is emerging as the next big wave of digital presence for billions of devices on the Internet. Smart cities are a practical manifestation of IoT, with the goal of efficient, reliable, and safe delivery of city utilities like water, power, and transport to residents, through their intelligent management. A data‐driven IoT software platform is essential for realizing manageable and sustainable smart utilities and for novel applications to be developed upon them. Here, we propose such service‐oriented software architecture to address 2 key operational activities in a smart utility: the IoT fabric for resource management and the data and application platform for decision‐making. Our design uses Open Web standards and evolving network protocols, cloud and edge resources, and streaming big data platforms. We motivate our design requirements using the smart water management domain; some of these requirements are unique to developing nations. We also validate the architecture within a campus‐scale IoT testbed at the Indian Institute of Science, Bangalore and present our experiences. Our architecture is scalable to a township or city while also generalizable to other smart utility domains. Our experiences serve as a template for other similar efforts, particularly in emerging markets and highlight the gaps and opportunities for a data‐driven IoT software architecture for smart cities. }, keywords = {}, pubstate = {published}, tppubtype = {article} } The Internet of things (IoT) is emerging as the next big wave of digital presence for billions of devices on the Internet. Smart cities are a practical manifestation of IoT, with the goal of efficient, reliable, and safe delivery of city utilities like water, power, and transport to residents, through their intelligent management. A data‐driven IoT software platform is essential for realizing manageable and sustainable smart utilities and for novel applications to be developed upon them. Here, we propose such service‐oriented software architecture to address 2 key operational activities in a smart utility: the IoT fabric for resource management and the data and application platform for decision‐making. Our design uses Open Web standards and evolving network protocols, cloud and edge resources, and streaming big data platforms. We motivate our design requirements using the smart water management domain; some of these requirements are unique to developing nations. We also validate the architecture within a campus‐scale IoT testbed at the Indian Institute of Science, Bangalore and present our experiences. Our architecture is scalable to a township or city while also generalizable to other smart utility domains. Our experiences serve as a template for other similar efforts, particularly in emerging markets and highlight the gaps and opportunities for a data‐driven IoT software architecture for smart cities. |
| 10. | Amrutur, Bharadwaj; Rajaraman, Vasanth; Acharya, Srikrishna; Ramesh, Rakshit; Joglekar, Ashish; Sharma, Abhay; Simmhan, Yogesh; Lele, Abhijit; Mahesh, Ashwin; Sankaran, Sathya An open Smart City IoT test bed: Street light poles as Smart City spines Conference Proceedings of the 2nd International Conference on Internet-of-Things Design and Implementation (IoTDI), 18.-21.04.17, Pittsburgh (USA), 2017. @conference{Amrutur2017, title = {An open Smart City IoT test bed: Street light poles as Smart City spines}, author = {Bharadwaj Amrutur and Vasanth Rajaraman and Srikrishna Acharya and Rakshit Ramesh and Ashish Joglekar and Abhay Sharma and Yogesh Simmhan and Abhijit Lele and Ashwin Mahesh and Sathya Sankaran}, url = {http://www.rbccps.org/wp-content/uploads/2017/10/p323-Amrutur.pdf}, doi = {10.1145/3054977.3057303}, year = {2017}, date = {2017-06-15}, booktitle = {Proceedings of the 2nd International Conference on Internet-of-Things Design and Implementation (IoTDI), 18.-21.04.17, Pittsburgh (USA)}, pages = {323-324}, abstract = {Street light poles will be a key enabler for a smart city's hardware infrastructure, thanks to their ubiquity throughout the city as well as access to power. We propose an IoT test bed around light poles for the city, with a modular hardware and software architecture to enable experimentation with various technologies.}, keywords = {}, pubstate = {published}, tppubtype = {conference} } Street light poles will be a key enabler for a smart city's hardware infrastructure, thanks to their ubiquity throughout the city as well as access to power. We propose an IoT test bed around light poles for the city, with a modular hardware and software architecture to enable experimentation with various technologies. |
| 11. | Chaturvedi, Shilpa; Tyagi, Sahil; Simmhan, Yogesh Collaborative reuse of streaming dataflows in IoT applications Conference Proceedings of the 13th International Conference on e-Science, 24.-27.10.17, Auckland (New Zealand), 2017. @conference{Chaturvedi2017, title = {Collaborative reuse of streaming dataflows in IoT applications}, author = {Shilpa Chaturvedi and Sahil Tyagi and Yogesh Simmhan}, url = {http://www.rbccps.org/wp-content/uploads/2018/12/08109159.pdf}, doi = {10.1109/eScience.2017.54}, year = {2017}, date = {2017-11-16}, booktitle = {Proceedings of the 13th International Conference on e-Science, 24.-27.10.17, Auckland (New Zealand)}, abstract = {Distributed Stream Processing Systems (DSPS) like Apache Storm and Spark Streaming enable composition of continuous dataflows that execute persistently over data streams. They are used by Internet of Things (IoT) applications to analyze sensor data from Smart City cyber-infrastructure, and make active utility management decisions. As the ecosystem of such IoT applications that leverage shared urban sensor streams continue to grow, applications will perform duplicate pre-processing and analytics tasks. This offers the opportunity to collaboratively reuse the outputs of overlapping dataflows, thereby improving the resource efficiency. In this paper, we propose dataflow reuse algorithms that given a submitted dataflow, identifies the intersection of reusable tasks and streams from a collection of running dataflows to form a merged dataflow. Similar algorithms to unmerge dataflows when they are removed are also proposed. We implement these algorithms for the popular Apache Storm DSPS, and validate their performance and resource savings for 35 synthetic dataflows based on public OPMW workflows with diverse arrival and departure distributions, and on 21 real IoT dataflows from RIoTBench. We see that our Reuse algorithms reduce the count of running tasks by 38 - 46% for the two workloads, and a reduction in cumulative CPU usage of 36-51%, that can result in real cost savings on Cloud resources.}, keywords = {}, pubstate = {published}, tppubtype = {conference} } Distributed Stream Processing Systems (DSPS) like Apache Storm and Spark Streaming enable composition of continuous dataflows that execute persistently over data streams. They are used by Internet of Things (IoT) applications to analyze sensor data from Smart City cyber-infrastructure, and make active utility management decisions. As the ecosystem of such IoT applications that leverage shared urban sensor streams continue to grow, applications will perform duplicate pre-processing and analytics tasks. This offers the opportunity to collaboratively reuse the outputs of overlapping dataflows, thereby improving the resource efficiency. In this paper, we propose dataflow reuse algorithms that given a submitted dataflow, identifies the intersection of reusable tasks and streams from a collection of running dataflows to form a merged dataflow. Similar algorithms to unmerge dataflows when they are removed are also proposed. We implement these algorithms for the popular Apache Storm DSPS, and validate their performance and resource savings for 35 synthetic dataflows based on public OPMW workflows with diverse arrival and departure distributions, and on 21 real IoT dataflows from RIoTBench. We see that our Reuse algorithms reduce the count of running tasks by 38 - 46% for the two workloads, and a reduction in cumulative CPU usage of 36-51%, that can result in real cost savings on Cloud resources. |
| 12. | Varshney, Prateeksha; Simmhan, Yogesh Demystifying fog computing: Characterizing architectures, applications and abstractions Conference Proceedings of the 1st International Conference on Fog and Edge Computing (ICFEC), 14.-15.05.17, Madrid (Spain), 2017. @conference{Varshney2017, title = {Demystifying fog computing: Characterizing architectures, applications and abstractions}, author = {Prateeksha Varshney and Yogesh Simmhan}, url = {http://www.rbccps.org/wp-content/uploads/2018/12/08014367.pdf}, doi = {10.1109/ICFEC.2017.20}, year = {2017}, date = {2017-08-24}, booktitle = {Proceedings of the 1st International Conference on Fog and Edge Computing (ICFEC), 14.-15.05.17, Madrid (Spain)}, abstract = {Internet of Things (IoT) has accelerated the deployment of millions of sensors at the edge of the network, through Smart City infrastructure and lifestyle devices. Cloud computing platforms are often tasked with handling these large volumes and fast streams of data from the edge. Recently, Fog computing has emerged as a concept for low-latency and resource-rich processing of these observation streams, to complement Edge and Cloud computing. In this paper, we review various dimensions of system architecture, application characteristics and platform abstractions that are manifest in this Edge, Fog and Cloud eco-system. We highlight novel capabilities of the Edge and Fog layers, such as physical and application mobility, privacy sensitivity, and a nascent runtime environment. IoT application case studies based on first-hand experiences across diverse domains drive this categorization. We also highlight the gap between the potential and the reality of Fog computing, and identify challenges that need to be overcome for the solution to be sustainable. Taken together, our article can help platform and application developers bridge the gap that remains in making Fog computing viable.}, keywords = {}, pubstate = {published}, tppubtype = {conference} } Internet of Things (IoT) has accelerated the deployment of millions of sensors at the edge of the network, through Smart City infrastructure and lifestyle devices. Cloud computing platforms are often tasked with handling these large volumes and fast streams of data from the edge. Recently, Fog computing has emerged as a concept for low-latency and resource-rich processing of these observation streams, to complement Edge and Cloud computing. In this paper, we review various dimensions of system architecture, application characteristics and platform abstractions that are manifest in this Edge, Fog and Cloud eco-system. We highlight novel capabilities of the Edge and Fog layers, such as physical and application mobility, privacy sensitivity, and a nascent runtime environment. IoT application case studies based on first-hand experiences across diverse domains drive this categorization. We also highlight the gap between the potential and the reality of Fog computing, and identify challenges that need to be overcome for the solution to be sustainable. Taken together, our article can help platform and application developers bridge the gap that remains in making Fog computing viable. |
| 13. | Zhou, Qunzhi; Simmhan, Yogesh; Prasanna, Viktor Knowledge-infused and consistent Complex Event Processing over real-time and persistent streams Journal Article Future Generation Computer Systems, 76 , pp. 391-406, 2017. @article{Zhou2017, title = {Knowledge-infused and consistent Complex Event Processing over real-time and persistent streams}, author = {Qunzhi Zhou and Yogesh Simmhan and Viktor Prasanna}, url = {http://www.rbccps.org/wp-content/uploads/2018/12/1-s2.0-S0167739X16304769-main.pdf}, doi = {10.1016/j.future.2016.10.030}, year = {2017}, date = {2017-11-30}, journal = {Future Generation Computer Systems}, volume = {76}, pages = {391-406}, abstract = {Emerging applications in Internet of Things (IoT) and Cyber–Physical Systems (CPS) present novel challenges to Big Data platforms for performing online analytics. Ubiquitous sensors from IoT deployments are able to generate data streams at high velocity, that include information from a variety of domains, and accumulate to large volumes on disk. Complex Event Processing (CEP) is recognized as an important real-time computing paradigm for analyzing continuous data streams. However, existing work on CEP is largely limited to relational query processing, exposing two distinctive gaps for query specification and execution: (1) infusing the relational query model with higher level knowledge semantics, and (2) seamless query evaluation across temporal spaces that span past, present and future events. These allow accessible analytics over data streams having properties from different disciplines, and help span the velocity (real-time) and volume (persistent) dimensions. In this article, we introduce a Knowledge-infused CEP (x-CEP) framework that provides domain-aware knowledge query constructs along with temporal operators that allow end-to-end queries to span across real-time and persistent streams. We translate this query model to efficient query execution over online and offline data streams, proposing several optimizations to mitigate the overheads introduced by evaluating semantic predicates and in accessing high-volume historic data streams. In particular, we also address temporal consistency issues that arise during fault recovery of query plans that span the boundary between real-time and persistent streams. The proposed x-CEP query model and execution approaches are implemented in our prototype semantic CEP engine, SCEPter. We validate our query model using domain-aware CEP queries from a real-world Smart Power Grid application, and experimentally analyze the benefits of our optimizations for executing these queries, using event streams from a campus-microgrid IoT deployment. Our results show that we are able to sustain a processing throughput of 3,000 events/secs for x-CEP queries, a 30x improvement over the baseline and sufficient to support a Smart Township, and can resume consistent processing within secs after stream outages as long as 2 hours.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Emerging applications in Internet of Things (IoT) and Cyber–Physical Systems (CPS) present novel challenges to Big Data platforms for performing online analytics. Ubiquitous sensors from IoT deployments are able to generate data streams at high velocity, that include information from a variety of domains, and accumulate to large volumes on disk. Complex Event Processing (CEP) is recognized as an important real-time computing paradigm for analyzing continuous data streams. However, existing work on CEP is largely limited to relational query processing, exposing two distinctive gaps for query specification and execution: (1) infusing the relational query model with higher level knowledge semantics, and (2) seamless query evaluation across temporal spaces that span past, present and future events. These allow accessible analytics over data streams having properties from different disciplines, and help span the velocity (real-time) and volume (persistent) dimensions. In this article, we introduce a Knowledge-infused CEP (x-CEP) framework that provides domain-aware knowledge query constructs along with temporal operators that allow end-to-end queries to span across real-time and persistent streams. We translate this query model to efficient query execution over online and offline data streams, proposing several optimizations to mitigate the overheads introduced by evaluating semantic predicates and in accessing high-volume historic data streams. In particular, we also address temporal consistency issues that arise during fault recovery of query plans that span the boundary between real-time and persistent streams. The proposed x-CEP query model and execution approaches are implemented in our prototype semantic CEP engine, SCEPter. We validate our query model using domain-aware CEP queries from a real-world Smart Power Grid application, and experimentally analyze the benefits of our optimizations for executing these queries, using event streams from a campus-microgrid IoT deployment. Our results show that we are able to sustain a processing throughput of 3,000 events/secs for x-CEP queries, a 30x improvement over the baseline and sufficient to support a Smart Township, and can resume consistent processing within secs after stream outages as long as 2 hours. |
| 14. | Shukla, Anshu; Chaturvedi, Shilpa; Simmhan, Yogesh RIoTBench: An IoT benchmark for distributed stream processing systems Journal Article Concurrency and Computation: Practice and Experience, 29 (21), 2017. @article{Shukla2017b, title = {RIoTBench: An IoT benchmark for distributed stream processing systems}, author = {Anshu Shukla and Shilpa Chaturvedi and Yogesh Simmhan}, url = {http://www.rbccps.org/wp-content/uploads/2018/12/Shukla_et_al-2017-Concurrency_and_Computation3A_Practice_and_Experience.pdf}, doi = {10.1002/cpe.4257}, year = {2017}, date = {2017-11-10}, journal = {Concurrency and Computation: Practice and Experience}, volume = {29}, number = {21}, abstract = {The Internet of Things (IoT) is an emerging technology paradigm where millions of sensors and actuators help monitor and manage physical, environmental, and human systems in real time. The inherent closed‐loop responsiveness and decision making of IoT applications make them ideal candidates for using low latency and scalable stream processing platforms. Distributed stream processing systems (DSPS) hosted in cloud data centers are becoming the vital engine for real‐time data processing and analytics in any IoT software architecture. But the efficacy and performance of contemporary DSPS have not been rigorously studied for IoT applications and data streams. Here, we propose RIoTBench, a real‐time IoT benchmark suite, along with performance metrics, to evaluate DSPS for streaming IoT applications. The benchmark includes 27 common IoT tasks classified across various functional categories and implemented as modular microbenchmarks. Further, we define four IoT application benchmarks composed from these tasks based on common patterns of data preprocessing, statistical summarization, and predictive analytics that are intrinsic to the closed‐loop IoT decision‐making life cycle. These are coupled with four stream workloads sourced from real IoT observations on smart cities and smart health, with peak streams rates that range from 500 to 10 000 messages/second from up to 3 million sensors. We validate the RIoTBench suite for the popular Apache Storm DSPS on the Microsoft Azure public cloud and present empirical observations. This suite can be used by DSPS researchers for performance analysis and resource scheduling, by IoT practitioners to evaluate DSPS platforms, and even reused within IoT solutions. }, keywords = {}, pubstate = {published}, tppubtype = {article} } The Internet of Things (IoT) is an emerging technology paradigm where millions of sensors and actuators help monitor and manage physical, environmental, and human systems in real time. The inherent closed‐loop responsiveness and decision making of IoT applications make them ideal candidates for using low latency and scalable stream processing platforms. Distributed stream processing systems (DSPS) hosted in cloud data centers are becoming the vital engine for real‐time data processing and analytics in any IoT software architecture. But the efficacy and performance of contemporary DSPS have not been rigorously studied for IoT applications and data streams. Here, we propose RIoTBench, a real‐time IoT benchmark suite, along with performance metrics, to evaluate DSPS for streaming IoT applications. The benchmark includes 27 common IoT tasks classified across various functional categories and implemented as modular microbenchmarks. Further, we define four IoT application benchmarks composed from these tasks based on common patterns of data preprocessing, statistical summarization, and predictive analytics that are intrinsic to the closed‐loop IoT decision‐making life cycle. These are coupled with four stream workloads sourced from real IoT observations on smart cities and smart health, with peak streams rates that range from 500 to 10 000 messages/second from up to 3 million sensors. We validate the RIoTBench suite for the popular Apache Storm DSPS on the Microsoft Azure public cloud and present empirical observations. This suite can be used by DSPS researchers for performance analysis and resource scheduling, by IoT practitioners to evaluate DSPS platforms, and even reused within IoT solutions. |
| 15. | Sharma, Abhay; Acharya, Srikrishna; Rajaraman, Vasanth; Ramesh, Rakshit; Babu, Arun; Amrutur, Bharadwaj Schemas for IoT interoperability for Smart Cities Presentation 09.11.2017. @misc{Sharma2017, title = {Schemas for IoT interoperability for Smart Cities}, author = {Abhay Sharma and Srikrishna Acharya and Vasanth Rajaraman and Rakshit Ramesh and Arun Babu and Bharadwaj Amrutur}, editor = {BuildSys '17: Proceedings of the 4th ACM International Conference on Systems for Energy-Efficient Built Environments}, url = {https://cps.iisc.ac.in/wp-content/uploads/2020/10/Schemas-for-IoT-interoperability-for-Smart-Cities.pdf}, doi = {https://doi.org/10.1145/3137133.3141466}, year = {2017}, date = {2017-11-09}, booktitle = {Proceedings of the 15th ACM Conference on Embedded Networked Sensor Systems, 05.-09.11.17, Delft (The Netherlands)}, abstract = {One of the key aspects of smart city ecosystem is enabling easy collection and exchange of data to develop new applications. Providing good, open APIs for smart city middleware along with standardising the data schemas will be vital for application and devise ecosystem to evolve. In this paper we present the resource catalogue component of the middleware along with a framework to develop data schemas for IoT devices. Using data schemas one can provide meta-data which enables effective use of the device data.}, keywords = {}, pubstate = {published}, tppubtype = {presentation} } One of the key aspects of smart city ecosystem is enabling easy collection and exchange of data to develop new applications. Providing good, open APIs for smart city middleware along with standardising the data schemas will be vital for application and devise ecosystem to evolve. In this paper we present the resource catalogue component of the middleware along with a framework to develop data schemas for IoT devices. Using data schemas one can provide meta-data which enables effective use of the device data. |
| 16. | Amrutur, Bharadwaj; Darbari, Hemant Summary report on the project "Study of India appropriate technology (IoT) solutions for Smart Cities" Technical Report 2017. @techreport{Amrutur2017b, title = {Summary report on the project "Study of India appropriate technology (IoT) solutions for Smart Cities"}, author = {Bharadwaj Amrutur and Hemant Darbari}, url = {http://www.rbccps.org/wp-content/uploads/2018/10/IISc_IoT4SmartCities_Summary_Report.pdf}, year = {2017}, date = {2017-05-20}, abstract = {The main objectives of our project are: (1) Recommendation and guidelines for Smart City RFPs related to IoT specific technologies, driven by India specific use case analysis and emerging technology adoption methodology, and (2) India appropriate reference architecture for IoT enabled Smart cities through a collaborative platform of domain experts from industry, academia, government, start-ups, professional bodies and user agencies. We conducted two workshops with City administrators: One in Chandigarh and another in Electronics City, to understand the city’s requirements. A series of telecons/webcons were held with technical presentations from a diverse set of domain experts from industry, academia, government, startups, etc. Further deliberations and discussions were done to synthesize the view points in this report.}, keywords = {}, pubstate = {published}, tppubtype = {techreport} } The main objectives of our project are: (1) Recommendation and guidelines for Smart City RFPs related to IoT specific technologies, driven by India specific use case analysis and emerging technology adoption methodology, and (2) India appropriate reference architecture for IoT enabled Smart cities through a collaborative platform of domain experts from industry, academia, government, start-ups, professional bodies and user agencies. We conducted two workshops with City administrators: One in Chandigarh and another in Electronics City, to understand the city’s requirements. A series of telecons/webcons were held with technical presentations from a diverse set of domain experts from industry, academia, government, startups, etc. Further deliberations and discussions were done to synthesize the view points in this report. |
