In this paper we present new optimization formulations for maximizing the network lifetime in wireless mesh networks performing data aggregation and dissemination for machine-to-machine communication in the Internet of Things. We focus on heterogeneous networks in which multiple applications co-exist and nodes may take on different roles for different applications. Moreover, we address network reconfiguration as a means to increase the network lifetime, in keeping with the current trend towards software defined networks and network function virtualization. To test our optimization formulations, we conducted a numerical study using randomly-generated mesh networks from 10 to 30 nodes, and showed that the network lifetime can be increased using network reconfiguration by up to 75 over a single, minimal-energy configuration. Further, our solutions are feasible to implement in practical scenarios: only few configurations are needed, thus requiring little storage for a standalone network, and the synchronization and signalling needed to switch configurations is low relative to each configuration's operating time.
The severe nature of underwater channel poses a great challenge for prolonging underwater acoustic sensor networks (UASNs) lifetime and achieving a reliable communication performance. Traditional approaches to improve the reliability such as automatic repeat request (ARQ) negatively affect the network lifetime (NL) due to energy dissipation caused by ARQ retransmission. A forward error correction (FEC) technique called fountain codes (FCs) can solve the energy efficiency problem of ARQ by transmitting both the original packet and some redundant packets to ensure a targeted reliability with few or no retransmissions. In this paper, we investigate performances of both traditional ARQ- and FC-based FEC methods in terms of NL, end-to-end delay, energy consumption, and frame error rate (FER) for UASNs. In this context, we abstract energy dissipation characteristics of conventional ARQ- and FC-based FEC method at the link-layer. We propose an integer linear programming (ILP) framework that maximizes the NL, which is operated on top of developed link-layer energy consumption models. Our results reveal that FC-based FEC methods can prolong the NL at a minimum of 16 while end-to-end delay, energy consumption, and FER can be reduced at least by 11 , 14 , and 9 as compared to classical ARQ, respectively.  Abstract Energy is one of the scarcest resources in wireless sensor network (WSN). One fundamental way of conserving energy is judicious deployment of sensor nodes within the network area so that energy flow remains balanced throughout the network. This avoids the problem of occurrence of ‘energy holes’ and ensures prolonged network lifetime. We have first investigated the problem for enhancing network lifetime using homogeneous sensor nodes. From our observation it is revealed that energy imbalance in WSN occurs due to relaying of data from different parts of the network towards sink. So for improved energy balance instead of using only sensor nodes it is desirable to deploy relay nodes in addition to sensor nodes to manage such imbalance. We have also developed a location-wise pre-determined heterogeneous node deployment strategy based on the principle of energy balancing derived from this analysis, leading to an enhancement of network lifetime. Exhaustive simulation is performed primarily to measure the extent of achieving our design goal of enhancing network lifetime while attaining energy balancing and maintaining coverage. The simulation results also show that our scheme does not compromise with other network performance metrics such as end-to-end delay, packet loss, throughput while achieving the design goal. Finally all the results are compared with two competing schemes and the results confirm our scheme's supremacy in terms of both design performance metrics as well as network performance metrics.  Wireless distributed microsensor systems will enable the reliable monitoring of a variety of environments for both civil and military applications. In this paper, we look at communication protocols, which can have significant impact on the overall energy dissipation of these networks. Based on our findings that the conventional protocols of direct transmission, minimum-transmission-energy, multi-hop routing, and static clustering may not be optimal for sensor networks, we propose LEACH (Low-Energy Adaptive Clustering Hierarchy), a clustering-based protocol that utilizes randomized rotation of local cluster based station (cluster-heads) to evenly distribute the energy load among the sensors in the network. LEACH uses localized coordination to enable scalability and robustness for dynamic networks, and incorporates data fusion into the routing protocol to reduce the amount of information that must be transmitted to the base station. Simulations show the LEACH can achieve as much as a factor of 8 reduction in energy dissipation compared with conventional outing protocols. In addition, LEACH is able to distribute energy dissipation evenly throughout the sensors, doubling the useful system lifetime for the networks we simulated. A suitable clustering algorithm for grouping sensor nodes can increase the energy efficiency of WSNs. However, clustering requires additional overhead, such as cluster head selection and assignment, and cluster construction. This paper proposes a new regional energy aware clustering method using isolated nodes for WSNs, called Regional Energy Aware Clustering with Isolated Nodes (REAC-IN). In REAC-IN, CHs are selected based on weight. Weight is determined according to the residual energy of each sensor and the regional average energy of all sensors in each cluster. Improperly designed distributed clustering algorithms can cause nodes to become isolated from CHs. Such isolated nodes communicate with the sink by consuming excess amount of energy. To prolong network lifetime, the regional average energy and the distance between sensors and the sink are used to determine whether the isolated node sends its data to a CH node in the previous round or to the sink. The simulation results of the current study revealed that REAC-IN outperforms other clustering algorithms. Majority of wireless sensor networks (WSNs) clustering protocols in literature have focused on extending network lifetime and little attention has been paid to the coverage preservation as one of the QoS requirements along with network lifetime. In this paper, an algorithm is proposed to be integrated with clustering protocols to improve network lifetime as well as preserve network coverage in heterogeneous wireless sensor networks (HWSNs) where sensor nodes can have different sensing radii and energy attributes. The proposed algorithm works in proactive way to preserve network coverage and extend network lifetime by efficiently leveraging mobility to optimize the average coverage rate using only the nodes that are already deployed in the network. Simulations are conducted to validate the proposed algorithm by showing improvement in network lifetime and enhanced full coverage time with less energy consumption Wireless sensor network (WSN) brings a new paradigm of real-time embedded systems with limited computation, communication, memory, and energy resources that are being used for huge range of applications where the traditional infrastructure-based network is mostly infeasible. The sensor nodes are densely deployed in a hostile environment to monitor, detect, and analyze the physical phenomenon and consume considerable amount of energy while transmitting the information. It is impractical and sometimes impossible to replace the battery and to maintain longer network life time. So, there is a limitation on the lifetime of the battery power and energy conservation is a challenging issue. Appropriate cluster head (CH) election is one such issue, which can reduce the energy consumption dramatically. Low energy adaptive clustering hierarchy (LEACH) is the most famous hierarchical routing protocol, where the CH is elected in rotation basis based on a probabilistic threshold value and only CHs are allowed to send the information to the base station (BS). But in this approach, a super-CH (SCH) is elected among the CHs who can only send the information to the mobile BS by choosing suitable fuzzy descriptors, such as remaining battery power, mobility of BS, and centrality of the clusters. Fuzzy inference engine (Mamdani’s rule) is used to elect the chance to be the SCH. The results have been derived from NS-2 simulator and show that the proposed protocol performs better than the LEACH protocol in terms of the first node dies, half node alive, better stability, and better lifetime.