Utility-Based Routing in Wireless Sensor Networks

Abstract

Wireless sensor networks (WSNs) have been proposed for monitoring physical environments. The applications in WSNs have comprised a wide variety of scenarios. The design of routing protocols in WSNs becomes more complicated than the traditional network when we consider the energy cost, throughput, reliability, and delay as routing metrics. Selecting a particular routing protocol mainly depends on the capabilities of the nodes, and on the requirements of the application. In this chapter, we will briefly discuss the existing utility-based routing protocols for WSNs. We put them into several categories according to their utility properties, such as delay, cost, and packet delivery ratio. In addition, we will also cover the composition-based utility for wireless networks and its extensions in low duty-cycle WSNs.

An Adaptive Energy-Efficient Uneven Clustering Routing Protocol for WSNs

“…In this paper, the proposed AEBUC algorithm is simulated and compared with the EEUC [15], DEBUC [16] algorithm under the same conditions through MATLAB 2020a. We designed three experiments to validate the routing protocols proposed in this paper.…”

“…Table 1 shows the relevant experimental environment and parameter settings for WSN routing initialization, CH selection, and data processing. The parameters related to the energy consumption model are taken from the literature [10], [15], [16], and other parameters are found by multiple simulation experiments to find their optimal values.…”

“…Early mainstream multi-hop uneven cluster routing protocols [14] set different competition radius based on the distance between nodes and BS to limit the cluster size and solve the "energy hole" problem. Li C. et al [15] proposed energyefficient uneven clustering protocol (EEUC). This protocol combines uneven clustering and multi-hop ideas, and uses the uneven competitive radius clustering method to achieve more pairs of clusters close to the BS and a relatively small number of ordinary nodes, so that these CHs can better save energy and achieve energy-balanced inter-cluster communication, which effectively solves the "energy hole" problem.…”

“…It sets different competition radius based on the candidate CH positions, and uses the greedy algorithm to find the optimal multi-hop data transmission path in the CH, effectively reducing each node's energy consumption and extending the network lifecycle. Literature [15], [16] in CH competition, due to the need to set different competition radius, the candidate CH broadcast more rounds, which will consume more energy; in addition, the CH selection algorithms in such literature do not consider factors such as node residual energy and node density, and the final CH selected is not necessarily the optimal CH.…”

Optimized Resource Allocation for Utility-Based Routing in Ad Hoc and Sensor Networks

“…An ordinary package is usually mailed through a regular service. The utility model proposed in [1] is then extended to be used in designs of various type of routings, e.g., opportunistic routing [6,7], data gathering tree [8], routing for duty-cycle [9,10] and delay-tolerant sensor networks [11]. However, the utility models in these work have several drawbacks.…”