Federated sensor networks (FSNs) connect and combine several partitioned wireless sensor networks (WSNs) to extend the scope of WSNs to larger scale geographical areas. The federated and sparsely/intermittently connected nature of FSNs introduce several challenges for deploying middleware services such as routing, querying, tracking, time synchronization. In this paper, we investigate the challenges for deploying a querying service on FSNs. We review several querying protocols proposed in the WSNs literature and identify the applicability and shortcomings of these protocols for FSNs. Based on our investigation, we suggest open research directions for building an efficient querying service for FSNs.
A Federated Sensor Network (FSN) is a network of geographically distributed Wireless Sensor Networks (WSNs) called islands. For querying on an FSN, we introduce the Layered Federated Sensor Network (L-FSN) Protocol. For layered management, L-FSN provides communication among islands by its inter-island querying protocol by which a query packet routing path is determined according to some path selection policies. L-FSN allows autonomous management of each island by island-specific intra-island querying protocols that can be selected according to island properties. We evaluate the applicability of L-FSN and compare the L-FSN protocol with various querying protocols running on the flat federation model. Flat federation is a method to federate islands by running a single querying protocol on an entire FSN without distinguishing communication among and within islands. For flat federation, we select a querying protocol from geometrical, hierarchical cluster-based, hash-based, and tree-based WSN querying protocol categories. We found that a layered federation of islands by L-FSN increases the querying performance with respect to energy-efficiency, query resolving distance, and query resolving latency. Moreover, L-FSN's flexibility of choosing intra-island querying protocols regarding the island size brings advantages on energy-efficiency and query resolving latency.
Due to the failure-prone and vulnerable structure of WSN nodes, understanding the typical activity patterns of nodes helps identify the faulty and malicious node activities and differentiate normal node behaviors from abnormal node behaviors. In this study, for understanding the typical node activities, we observe the effects of the network load on energy consumption, packet throughput, and latency parameters. We run simulations of networks with a variable number of sinks up to 5 in a network of various sizes. We observed a growth in the network load as the source and sink node request activities increased. We found that increasing the number of sinks affects the overall network load and causes communication delays between the source and sink node.
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