Approximation algorithm for data broadcasting in duty cycled multi-hop wireless networks

Abstract

Broadcast is a fundamental operation in wireless networks. To this end, many past studies have studied the NP-hard, broadcast problem for always-on multi-hop networks. However, in wireless sensor networks, nodes are powered by batteries, meaning, they have finite energy. Consequently, nodes are required to have a low duty cycle, whereby they switch between active and sleep state periodically. This means that a transmission from a node may not reach all of its neighbors simultaneously. Consequently, any developed broadcast protocols must consider collisions and the wakeup times of neighboring nodes. Henceforth, this paper studies the minimum latency broadcast scheduling problem in duty cycled multi-hop wireless networks (MLBSDC), which remains NP hard. The MLBSDC problem aims to find a collision-free schedule that minimizes the time in which the last node receives a broadcast message. We propose a novel algorithm called CFBS that allows nodes in different layers of the broadcast tree to transmit simultaneously. We prove that CFBS produces a latency of at most (T + 1)H + T O(log 2 H). Here, T denotes the number of time slots in a scheduling period, and H is the optimal broadcast latency obtained from the shortest path tree algorithm assuming no collision. We also show that the total number of transmissions is at most 4(T + 2) times larger than the optimal value. The results from extensive simulation show that CFBS has a better performance than OTAB, the best broadcast scheduling algorithm to date. In particular, the broadcast latency achieved by CFBS is up to 3 20 that of OTAB.

Distributed low‐latency broadcast scheduling for multi‐channel duty‐cycled wireless IoT networks

“…The OTAB algorithm was proven to have a ratio of 17|T|. Afterward, Zhao et al 19 proposed a broadcasting algorithm based on CDS (connected dominating set) technique with a latency upper bound of (T + 1)H + TO(log 2 H),…”

“…The works in References 1,17–22 have studied the MLBS problem in duty‐cycled wireless IoT networks. The work in Reference 17 first proved that such a problem is NP‐hard and introduced two approximate algorithms based on D2 coloring technique with approximation ratios of $$$ O\left({\Delta}^2+1\right) $$$ and $$$ 24\mid T\mid +1 $$$ respectively, where $$$ \Delta $$$ denotes the maximum degree of nodes in the network and $$$ \mid T\mid $$$ represents the total amount of active time slots in a working cycle.…”

“…The OTAB algorithm was proven to have a ratio of $$$ 17\mid T\mid $$$. Afterward, Zhao et al 19 proposed a broadcasting algorithm based on CDS (connected dominating set) technique with a latency upper bound of $$$ \left(T+1\right)H+ TO\left({\log}_2H\right) $$$, where $$$ H $$$ denotes the height of the broadcast tree. Then, the work in Reference 20 proposed a latency‐aware broadcast algorithm relying on the geometrical unrelated set.…”

“…The broadcast latency is determined by the final time slot in which the message is successfully received by one of the leaf nodes. To reduce the broadcast latency, the works in References 17–22 have investigated the MLBS problem in duty‐cycled networks. These studies involve a separated consideration between the scheduling of nodes and the design of the broadcast tree.…”

Optimizing Packet Generation Rate for Multiple Hops WBAN with CSMA/CA Based on IEEE802.15.6

“…ad hoc network, mobile network, ITS system and so on [8]- [11]. The MAC layer, PHY layer, network layer and crosslayer of multiple hops scheme also are researched [12]- [15].…”