This paper presents a survey on the current state-of-the-art in Wireless Sensor Network (WSN) Operating Systems (OSs). In recent years, WSNs have received tremendous attention in the research community, with applications in battlefields, industrial process monitoring, home automation, and environmental monitoring, to name but a few. A WSN is a highly dynamic network because nodes die due to severe environmental conditions and battery power depletion. Furthermore, a WSN is composed of miniaturized motes equipped with scarce resources e.g., limited memory and computational abilities. WSNs invariably operate in an unattended mode and in many scenarios it is impossible to replace sensor motes after deployment, therefore a fundamental objective is to optimize the sensor motes’ life time. These characteristics of WSNs impose additional challenges on OS design for WSN, and consequently, OS design for WSN deviates from traditional OS design. The purpose of this survey is to highlight major concerns pertaining to OS design in WSNs and to point out strengths and weaknesses of contemporary OSs for WSNs, keeping in mind the requirements of emerging WSN applications. The state-of-the-art in operating systems for WSNs has been examined in terms of the OS Architecture, Programming Model, Scheduling, Memory Management and Protection, Communication Protocols, Resource Sharing, Support for Real-Time Applications, and additional features. These features are surveyed for both real-time and non-real-time WSN operating systems.
In this paper, we present a Multi-hop Routing with Low Energy Adaptive Clustering Hierarchy (MR-LEACH) protocol. In order to prolong the lifetime of Wireless Sensor Network (WSN),
MR-LEACH partitions the network into different layers of clusters. Cluster heads in each layer collaborates with the adjacent layers to transmit sensor's data to the base station. Ordinary sensor nodes join cluster heads based on the Received Signal Strength Indicator (RSSI). The transmission of nodes is controlled by a Base Station (BS) that defines the Time Division Multiple Access (TDMA) schedule for each cluster-head. BS selects the upper layers cluster heads to act as super cluster heads for lower layer cluster heads.Thus, MR-LEACH follows multi-hop routing from cluster-heads to a base station to conserve energy, unlike the LEACH protocol. Performance evaluation has shown that MR-LEACH achieves significant improvement in the LEACH protocol and provides energy efficient routing for WSN.
We highlight different important factors that must be considered for an effective available-bandwidth-based flow admission control algorithm in ad hoc wireless networks. Moreover, we present BandEst; it is a combination of a measurement-based available bandwidth estimation technique and a flow admission control algorithm for ad hoc IEEE 802.15.4-based ad hoc networks that considers the identified factors. Extensive simulations are performed to compare BandEst with the state-of-the-art availablebandwidth-based flow admission control algorithms for ad hoc wireless networks. Our simulation results demonstrate that BandEst significantly outperforms the state-of-the-art available-bandwidth-based flow admission control algorithms for ad hoc wireless networks.
Estimating the available bandwidth in IEEE 802.15.4-based networks is a difficult and challenging task due to the shared nature of the wireless communication medium. The MAC layer decides the sharing of a communication medium, therefore the MAC layer dictates the amount of bandwidth available to a node. Some recent solutions consider the impact of the MAC layer back-off due to collision and transmitter and receiver non-synchronization on the available bandwidth, Available Bandwidth Estimation (ABE) is one such example. None of the existing solutions pro-actively consider the impact of additional overhead of an unslotted Carrier Sense Multiple Access Collision Avoidance (CSMA-CA) protocol with an increased data load inside a network on the available bandwidth. Therefore the amount of reported available bandwidth is not fully available to a node, hence this can result in poor admission decisions. In this paper, we show that increasing data load inside the IEEE 802.15.4-based network increases MAC layer overhead. Afterwards, we enhance the ABE bandwidth estimation and admission control algorithms so that they pro-actively consider the additional MAC layer overhead associated with an increased data load inside a network. We performed a number of simulations, and our simulation results show that the proposed proactive ABE method performs better than the original ABE method.
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