CONETSI: On Demand Distributed Network State Information Collection using Opportunistic Exploration for Resource Constrained Networks | IEEE Conference Publication | IEEE Xplore

CONETSI: On Demand Distributed Network State Information Collection using Opportunistic Exploration for Resource Constrained Networks


Abstract:

Large scale IoT deployments for industrial, smart-city and many other applications require efficient mechanisms to monitor node health, and various performance influencin...Show More

Abstract:

Large scale IoT deployments for industrial, smart-city and many other applications require efficient mechanisms to monitor node health, and various performance influencing parameters of the underlying resource constrained network. Efficient and timely collection of such Network State Information (NSI) and its analytics help network operators ensure continuous operation, maintain end application QoS, and optimize the overall network performance through efficient network resource management. Considering the power and bandwidth constraints in these networks, it is imperative that the overheads inherently associated with NSI collection are minimized in transporting the monitored data comprising of different levels of demands and time criticality. We present CONETSI, a distributed algorithm and protocol for collecting NSI by forming node chains. Briefly, a node having NSI to be sent to a remote monitoring station opportunistically advertises for other potential sources of NSI. One of the neighboring nodes, chosen based on a distributed contention resolution logic running on the nodes, joins the chain. The exploration is then repeated by the joined nodes forming the NSI chain rooted at the originating node. The farthest node then collects NSI serially along the chain towards the originating node. CONETSI provides differential QoS to the NSI transfers by considering demand level and time criticality of the NSI data possessed by the network nodes. We evaluate theoretical bounds, backed by experimental results showing the performance gains that amortize the overheads associated with the exploration process. We also describe our software implementation in Contiki-NG operating system running the 6LoWPAN/RPL stack.
Date of Conference: 07-11 January 2020
Date Added to IEEE Xplore: 09 March 2020
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Conference Location: Bengaluru, India

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