Constrained Optimal Routing in Wireless Sensor Networks with Uncertain Network Connectivity
Keywords:
Wireless sensor networks; multihop routing; receiver energy; uncertain connectivity; route reliability; Goal Programming; energy-aware routing; constrained optimization.Abstract
Wireless sensor networks (WSNs) work under stringent energy constraints as the nodes are generally battery powered which may deploy in locations in which the replacement of the battery is difficult. The routing decisions does not only influence transmission energy but also dissipate energy at intermediate nodes and forward packets during multihop communication. Nevertheless, receiver energy can be an unavoidable component of multihop communication, which is frequently treated as implicit in energy-aware routing models. Additionally, practical WSNs experience uncertain wireless connectivity due to interference, obstruction, environmental conditions, fading, and node mobility. These factors make deterministic routing assumptions insufficient towards applications requiring reliable data delivery. Goal programming (GP) is used for a receiver-energy-aware constrained multi-hop routing framework under uncertain connectivity. The receiver-energy dissipation, total communication energy, residual-energy preservation, and route reliability are considered simultaneously. The route availability is integrated towards optimization along a logarithmic transformation, and the link availability is depicted probabilistically. The competing routing objectives are managed according to the predefined aspiration priority levels and aspiration levels. The excessive multihop forwarding, overuse of energy constrained relay nodes and unreliable links are addressed through the formulation. The additional hops decrease the distance-dependent transmission expenditure, but the electronic energy and cumulative receiver energy are increased. Likewise, the required route reliability limits the feasible routing alternatives and increases the energy expenditure. Therefore, the framework proposes a flexible mathematical basis along network lifetime considerations, receiver-energy consumption, connectivity reliability and balanced energy efficiency under uncertain WSN environments.
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