Abstract
Multicasting is a fundamental network service for one-to-many communications in wireless sensor networks. However, when the sensor nodes work in an asynchronous duty-cycled way, the sender may need to transmit the same message several times to one group of its neighboring nodes, which complicates the minimum energy multicasting problem. Thus, in this paper, we study the problem of minimum energy multicasting with adjusted power (the MEMAP problem) in the duty-cycled sensor networks, and we prove it to be NP-hard. To solve such a problem, the concept of an auxiliary graph is proposed to integrate the scheduling problem of the transmitting power and transmitting time slot and the constructing problem of the minimum multicast tree in MEMAP, and a greedy algorithm is proposed to construct such a graph. Based on the proposed auxiliary graph, an approximate scheduling and constructing algorithm with an approximation ratio of is proposed, where K is the number of destination nodes. Finally, the theoretical analysis and experimental results verify the efficiency of the proposed algorithm in terms of the energy cost and transmission redundancy.
Highlights
In recent years, wireless sensor networks (WSNs) have been used in monitoring and retrieving sensory data from the physical world [1,2,3,4,5,6,7,8,9,10,11], which are usually expected to last over several months or years
The minimum energy multicasting (MEM) problem is proposed, which seeks to disseminate the messages from the source node to all of the destination nodes with minimum energy cost
In this work, we study the problem of minimum energy multicasting with adjusted power (MEMAP) in duty-cycled sensor networks, and it is proven to be NP-hard
Summary
Wireless sensor networks (WSNs) have been used in monitoring and retrieving sensory data from the physical world [1,2,3,4,5,6,7,8,9,10,11], which are usually expected to last over several months or years. A schema of the duty-cycle is proposed in WSNs. According to the duty-cycle schema, each node switches between the active and the dormant state periodically; the period of the dormant state is much longer than that of the active state in order to save energy. The MEM problem has attracted extensive attentions from the research community, and it is studied in both nodes always-awake sensor networks [26,27,28,29,30,31,32] and duty-cycled sensor networks [33,34,35,36]. In the nodes always-awake sensor networks, where each node can deliver the massages to one group of its neighboring nodes by only one transmission, the MEM problem is proven to be NP-hard, and some approximation algorithms have been proposed [26,27,28,29,30,31,32]
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