TeaCP: A Toolkit for evaluation and analysis of collection protocols in Wireless Sensor Networks

Si, Wei; Hashemi, Morteza; Warsawski, Idan; Laifenfeld, Moshe; Starobinski, David; Trachtenberg, Ari

doi:10.1109/comcas.2013.6685292

Cited by 5 publications

(7 citation statements)

References 30 publications

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“…Different schemes have been proposed to provide energy and bandwidth-efficient designs for wireless sensor networks for data collection [11,[15][16][17][18]. Distributed Source Coding (DSC) with constrained Viterbi Algorithm (VA-DSC) with both convolutional and turbo codes which take advantage of known parity bits to increase the decoding performance while reducing decoding errors and computational complexity.…”

Section: Related Workmentioning

confidence: 99%

“…They also developed an event recorder for the stakeholders using android phones in order to gather more information of the system. A prototype toolkit developed by Si et al [18], named TeaCP, has been used for evaluation and analysis of collection protocols. The toolkit includes packet generation rates and transmission power for testing protocols, visualization of packet routes, network topology and other statistics.…”

Section: Related Workmentioning

confidence: 99%

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A case study of an autonomous wireless sensor network system for environmental data collection

Dong

Meyland

Karaomeroglu

2017

Env Prog and Sustain Energy

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This article presents a case study of the design of an autonomous wireless sensor network for environmental monitoring to provide data for understanding the relationships among food, energy, and water systems in suburban areas in Long Island New York. The study focuses on the existing water quality data for the two counties on Long Island, Nassau and Suffolk Counties, to understand the impact of energy and food production on the coastal waters of Long Island Sound and Peconic Bay. The analysis of existing data from the US Environmental Protection Agency database reveals the challenges in using such data to understand the relationships between water quality, weather events and identified point sources of pollutants. Maintaining on-going data collection programs is expensive, time-consuming and personnel intensive which is why this project examines new ways to obtain and utilize environmental data. The researchers propose the design of an autonomous wireless sensor network environmental monitoring system with an optimal sensor placement strategy to identify targeted locations for water quality monitoring. The goal is to provide environmental data that can facilitate a better understanding of the interactions of farming activities and energy production resulting in undesirable impacts on water quality. The proposed design can be used to provide real-time data to help stakeholders improve efficiency in resource management and advance early detection of potential hazardous events. V C

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

A case study of an autonomous wireless sensor network system for environmental data collection

Dong

Meyland

Karaomeroglu

2017

Env Prog and Sustain Energy

View full text Add to dashboard Cite

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“…For the simulations, we use real RSSI (received signal strength indication) traces collected in an intra-car environment [4]. The simulation results demonstrate that Hybrid-BCP achieves higher reliability than Hybrid-CTP if both protocols use the same power transmission (e.g., 95% vs 88%).…”

Section: Introductionmentioning

confidence: 99%

“…For instance, node 10 can communicate with the sink either on Each node is connected to either a wired interface or a wireless interface or both. The data packets of the sensor nodes (1)(2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14) need to be delivered to the sink (node 0). the wired interface or the wireless interface.…”

Section: Introductionmentioning

confidence: 99%

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A Robust Load Balancing and Routing Protocol for Intra-Car Hybrid Wired/Wireless Networks

Starobinski

Laifenfeld

2019

IEEE Trans. on Mobile Comput.

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With the emergence of connected and autonomous vehicles, sensors are increasingly deployed within cars to support new functionalities. Traffic generated by these sensors congest traditional intra-car networks, such as CAN buses. Furthermore, the large amount of wires needed to connect sensors makes it harder to design cars in a modular way. To alleviate these limitations, we propose, simulate, and implement a hybrid wired/wireless architecture, in which each node is connected to either a wired interface or a wireless interface or both. Specifically, we propose a new protocol, called Hybrid-Backpressure Collection Protocol (Hybrid-BCP), to efficiently collect data from sensors in intra-car networks. Hybrid-BCP is backward-compatible with the CAN bus technology, and builds on the BCP protocol, designed for wireless sensor networks. Hybrid-BCP achieves high throughput and shows resilience to dynamic network conditions, including adversarial interferences. Our testbed implementation, based on CAN and ZigBee transceivers, demonstrates the load balancing and routing functionalities of Hybrid-BCP and its resilience to DoS attacks. We further provide simulation results, obtained with the ns-3 simulator and based on real intra-car RSSI traces, that compare between the performance of Hybrid-BCP and a tree-based data collection protocol. Notably, the simulations show that Hybrid-BCP can achieve the same performance as the tree-based protocol while reducing the radio transmission power by a factor of 10.

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Cyber‐physical network architecture for data stream provisioning in complex ecosystems

Okafor

Ndinechi

Misra

2021

Trans Emerging Tel Tech

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Intelligent fog cyber‐physical social systems (iFog CPSS) is a novel smart city project that uses intrinsic processes to automate microservices such as edge‐to‐fog or fog‐to‐cloud monitoring of complex real‐time activities. This article presents a dynamic cyber‐physical architecture that leverages iFog layers to map location‐based services (LBS) on a spine‐leaf datacenter clos topology. Individual edge clusters are connected to the edge‐fog layer, which communicates with iFog gateways for processing streams' requests. Use‐case application of artificial intelligence (AI) in vehicular ad‐hoc networks (VANETs) is introduced for data stream provisioning. In the validation study, a secure docker‐based iFog CPS experiment is carried out using traffic trace files from C++ modeller. iFog spine‐leaf architecture for fog‐computing and cloud‐computing are compared using two key metrics. For traffic workload utilization, the results show that 83.33% of the traffic workload is utilized at the Fog layer while 16.67% is consumed in the cloud layer. For latency profile, the results indicate that Fog and cloud streams had 20.31% and 77.69%, respectively. In terms of iFog VANET spine‐leaf congestion control, three distinct algorithms are studied, namely the proposed linear routing algorithm (LRA), LEACH, and collection tree protocol (CTP). In each case, the resource utilization for VANET gave 34.45%, 32.18%, and 33.37%, respectively. Latency response gave 11.76%, 82.35%, and 5.89%, respectively. Also, the throughput scenario offered 19.61%, 39.22%, and 41.17%, respectively. Consequently, the iFog scenario offers satisfactory LBS provisioning for VANETs clusters.

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TeaCP: A Toolkit for evaluation and analysis of collection protocols in Wireless Sensor Networks

Cited by 5 publications

References 30 publications

A case study of an autonomous wireless sensor network system for environmental data collection

A case study of an autonomous wireless sensor network system for environmental data collection

A Robust Load Balancing and Routing Protocol for Intra-Car Hybrid Wired/Wireless Networks

Cyber‐physical network architecture for data stream provisioning in complex ecosystems

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