Multi-Radio Wireless Sensor Networks: Energy Efficient Solutions for Radio Activation

Abstract

Consider a wireless sensor network where each node has K radios r 1, r2, · · · , rK such that the one hop reachability distance (resp. energy expended) of (resp. by) radio r i is greater than that of r j , 1 ≤ j < i ≤ K. Given such a network, the problem of energy efficient radio activation is to minimize the total energy spent by the active radios across all nodes in order to maintain a connected network. We show that this problem is NP-Hard. We initially pay attention to the case of K = 2 and discuss a basic version of the radio activation problem in such networks. We propose approximation methodologies for solving this problem. Our analytical and experimental studies reveal that the greedy algorithm and the minimum spanning tree solution have the best worst case performance while the greedy algorithm has the best average case performance. To the best of our knowledge, this is one of the first few works to focus on optimal radio activation in generic multi-radio wireless networks.

A joint resource allocation-channel coding design based on distributed source coding

“…Also, it can be seen that utilizing channel coding improves the bit error performance significantly because of error detection and correction capability that decoders are equipped with. Finally, we note that the RS (31,16) code demonstrates a better performance than Hamming (7,4), which is totally predictable because of the higher detecting and correcting capability of the RS (31,16) code with respect to that of the Hamming (7,4) code.…”

“…On the basis of the proposed approach described earlier and considering five different scenarios regarding the utilization of channel coding, we performed extensive simulations to evaluate the network performance in terms of information efficiency at the receiver end and energy consumption. The five scenarios include the following: (1) uncoded scheme; 2) coded scheme using Hamming (7,4) coding; (3) coded scheme using Hamming (31,26) coding; (4) coded scheme using RS (31,16); and (5) coded scheme using RS (7,5). We selected these schemes in order to evaluate the proposed joint design performance for different coding schemes, with different coding rates, lengths, and error detection/correction capabilities.…”

“…For instance, a seven-error correcting RS (31,16) is an RS code in which n D 31, k D 16, m D 5, t D 7, and d min D 15. Assuming hard decision decoding, the RS bit error probability in terms of the channel symbol error probability, p, is approximated as Figure 3 shows the bit error probability of M-PSK modulation over an AWGN channel as a function of SNR per bit, for different values of M and for three different scenarios, one without using channel coding, one using Hamming (7,4), and one using RS (31,16) with t D 7. We observe that for any given SNR per bit, the bit error performance deteriorates as M increases.…”

“…Some signal processing algorithms and hardware design can also be considered to deal with the energy efficiency problem in such networks. Recent studies [2][3][4][5][6][7][8] have been conducted on energy efficiency improvement in WSNs. For example, in [2], a single-cluster algorithm in homogeneous WSNs with one solar-powered sensor is proposed to optimize the network lifetime.…”

A Virtual Backbone Construction Heuristic for Maximizing the Lifetime of Dual-Radio Wireless Sensor Networks

“…In [1], the authors studied the problem of finding multiple backbones and scheduling the backbones to work for different time periods such that the network lifetime would be maximized. Hereafter, the multiple backbones used for different periods were called virtual backbones In recent studies, some researchers use sensors with multiple radios to minimize total energy consumption in wireless sensor networks [7], [8], [9]. In multiple-radio wireless sensor networks, sensors can be equipped with multiple radios to promote the capacity of wireless sensor networks, such as simultaneous data transmission and reception, and operations on different frequency bands.…”