Energy efficiency of virtual multi‐input,multi‐output based on sensor selection in wireless sensor networks

In this paper, a weighted node selection technique in wireless sensor networks is proposed. It is an energy‐efficient cooperative technique where a selected number of sensors at the transmitting end are connected with a selected number of sensors at the receiving end to form a virtual multi‐input multi‐output. The proposed technique is based on a weighted selection function that combines geographical location, inter‐sensor distance in a cluster, channel estimate energy, power circuit, channel loss, mobility factor, and residual energy of each sensor. The weight of each of these parameters in the selection function depends on the degree that this parameter affects the energy consumption. Then, the cluster head selects the sensors with better selection parameters that reduce the overall energy consumption. The numerical results show that the proposed weighted node selection technique achieves a significant improvement in the energy consumption, delay, and network lifetime than the conventional techniques with and without the selected number of sensors. Its improvement reaches 15% in the energy consumption that leads to an increase in the network lifetime by four times the network lifetime of other techniques. Copyright © 2012 John Wiley & Sons, Ltd.     

A delay‐centric parallel multi‐path routing protocol for cognitive radio ad hoc networks

In this paper, we develop a delay‐centric parallel multi‐path routing protocol for multi‐hop cognitive radio ad hoc networks. First, we analyze the end‐to‐end delay of multi‐path routing based on queueing theory and present a new dynamic traffic assignment scheme for multi‐path routing with the objective of minimizing end‐to‐end delay, considering both spectrum availability and link data rate. The problem is formulated as a convex problem and solved by a gradient‐based search method to obtain optimal traffic assignments. Furthermore, a heuristic decentralized traffic assignment scheme for multi‐path routing is presented. Then, based on the delay analysis and the 3D conflict graph that captures spectrum opportunity and interference among paths, we present a route discovery and selection scheme. Via extensive NS2‐based simulation, we show that the proposed protocol outperforms the benchmark protocols significantly and achieves the shortest end‐to‐end delay. Copyright © 2015 John Wiley & Sons, Ltd.     

Greedy construction of load‐balanced virtual backbones in wireless sensor networks

Inspired by the backbone concept in wired networks, a virtual backbone is expected to bring substantial benefits to routing in wireless sensor networks (WSNs). A connected dominating set (CDS) is used as a virtual backbone for efficient routing and broadcasting in WSNs. Most existing works focus on constructing a minimum CDS, a k‐connect m‐dominating CDS, a minimum routing cost CDS, or a bounded‐diameter CDS. However, the load‐balance factor is not considered for CDSs in WSNs. In this paper, a greedy‐based approximation algorithm is proposed to construct load‐balanced CDS in a WSN. More importantly, we propose a new problem: the Load‐balanced Allocate Dominatee problem. Consequently, we propose an optimal centralized algorithm and an efficient probability‐based distributed algorithm to solve the Load‐balanced Allocate Dominatee problem. For a given CDS, the upper and lower bounds of the performance ratio of the distributed algorithm are analyzed in the paper. Through extensive simulations, we demonstrate that our proposed methods extend network lifetime by up to 80% compared with the most recently published CDS construction algorithm. Copyright © 2012 John Wiley & Sons, Ltd.     

A distributed,multi‐hop,adaptive, tree‐based energy‐balanced routing approach

To accomplish the primary objective of data sensing and collection of wireless sensor networks (WSN), the design of an energy efficient routing algorithm is very important. However, the energy constrained sensing nodes along with the intrinsic properties of the (WSN) environment makes the routing a challenging task. To overcome this routing dilemma, an improved distributed, multi‐hop, adaptive, tree‐based energy‐balanced (DMATEB) routing scheme is proposed in this paper. In this scheme, a relay node is selected in view of minimum distance and high energy from a current sensing node. Further, the parent node is chosen among the selected relay nodes on the basis of high residual energy and less power consumption with due consideration of its associated child nodes. As each sensing node itself selects its parent among the available alternatives, the proposed scheme offers a distributive and adaptive approach. Moreover, the proposed system does not overload any selected parent of a particular branch as it starts acting as a child whenever its energy lowers among the other available relay nodes. This leads to uniform energy utilization of nodes that offers a better energy balance mechanism and improves the network lifespan by 20% to 30% as compared with its predecessors.     

A mode transformation algorithm based on traffic prediction in virtual multi‐OLT PON

In this paper, a mode transformation algorithm based on traffic prediction in virtual multiple optical line terminal (OLT) passive optical network (PON) is proposed. By proposing exponential smoothing algorithm based on weight update (WU‐ESA), user traffic is predicted well. WU‐ESA is a combination of two algorithms: exponential smoothing algorithm (ESA) and genetic algorithm (GA). The weight in ESA is optimized by GA based on real‐number encoding. By setting two periods, GA part and ESA part can be separated effectively. By presenting elastic packing algorithm (EPA), the load balance problem in virtual multi‐OLT PON is solved. EPA is implemented based on WU‐ESA. By the simulation and analysis, the effectiveness of the proposed algorithms is demonstrated. Compared with traditional mode transformation algorithm, EPA shows good performances in delay, throughput, and packet loss. Compared with traditional mode transformation algorithm, the EPA makes the packet loss decrease by at least 5% when the system load is greater than 0.9. Meanwhile, the delay of the two subsystems can be kept at a relatively balanced level by the implement of EPA. For throughput, the use of EPA improves the throughput by 20% when the system load is high.     

An energy‐efficient utility‐based distributed data routing scheme for heterogenous sensor networks

A utility‐based distributed data routing algorithm is proposed and evaluated for heterogeneous wireless sensor networks. It is energy efficient and is based on a game‐theoretic heuristic load‐balancing approach. It runs on a hierarchical graph arranged as a tree with parents and children. Sensor nodes are considered heterogeneous in terms of their generated traffic, residual energy and data transmission rate and the bandwidth they provide to their children for communication. The proposed method generates a data routing tree in which child nodes are joined to parent nodes in an energy‐efficient way. The principles of the Stackelberg game, in which parents as leaders and children as followers, are used to support the distributive nature of sensor networks. In this context, parents behave cooperatively and help other parents to adjust their loads, while children act selfishly. Simulation results indicate the proposed method can produce on average more load‐balanced trees, resulting in over 30% longer network lifetime compared with the cumulative algorithm proposed in the literature. Copyright © 2014 John Wiley & Sons, Ltd.     

Cross‐Layer Resource Allocation in Multi‐interface Multi‐channel Wireless Multi‐hop Networks

In this paper, an analytical framework is proposed for the optimization of network performance through joint congestion control, channel allocation, rate allocation, power control, scheduling, and routing with the consideration of fairness in multi‐channel wireless multi‐hop networks. More specifically, the framework models the network by a generalized network utility maximization (NUM) problem under an elastic link data rate and power constraints. Using the dual decomposition technique, the NUM problem is decomposed into four subproblems — flow control; next‐hop routing; rate allocation and scheduling; power control; and channel allocation — and finally solved by a low‐complexity distributed method. Simulation results show that the proposed distributed algorithm significantly improves the network throughput and energy efficiency compared with previous algorithms.     

Utility‐driven construction of balanced data routing trees in wireless sensor networks

In wireless sensor networks, achieving load balancing in an energy‐efficient manner to improve the network lifetime as much as possible is still a challenging problem because in such networks, the only energy resource for sensor nodes is their battery supplies. This paper proposes a game theoretical‐based solution in the form of a distributed algorithm for constructing load‐balanced routing trees in wireless sensor networks. In our algorithm, load balancing is realized by adjusting the number of children among parents as much as possible, where child adjustment is considered as a game between the parents and child nodes; parents are considered as cooperative players, and children are considered as selfish players. The gained utility by each node is determined by means of some utility functions defined per role, which themselves determine the behavior of nodes in each role. When the game is over, each node gains the maximum benefit on the basis of its utility function, and the balanced tree is constructed. The proposed method provides additional benefits when in‐network aggregation is applied. Analytical and simulation results are provided, demonstrating that our proposed algorithm outperform two recently proposed benchmarking algorithms [1, 2], in terms of time complexity and communication overhead required for constructing the load‐balanced routing trees. Copyright © 2012 John Wiley & Sons, Ltd.     

Load‐balanced data gathering in Internet of Things using an energy‐aware cuckoo‐search algorithm

This paper deals with the lifetime problem in the Internet of Things. We first propose an efficient cluster‐based scheme named “Cuckoo‐search Clustering with Two‐hop Routing Tree (CC‐TRT)” to develop a two‐hop load‐balanced data aggregation routing tree in the network. CC‐TRT uses a modified energy‐aware cuckoo‐search algorithm to fairly select the best cluster head (CH) for each cluster. The applied cuckoo‐search algorithm makes the CH role to rotate between different sensors round by round. Subsequently, we extend the CC‐TRT scheme to present two methods for constructing multi‐hop data aggregation routing trees, named “Cuckoo‐search Clustering with Multi‐Hop Routing Tree (CC‐MRT)” and “Cuckoo‐search Clustering with Weighted Multi‐hop Routing Tree (CC‐WMRT).” Both CC‐MRT and CC‐WMRT rely on a two‐level structure; they not only use an energy‐aware cuckoo‐search algorithm to fairly select the best CHs but also adopt a load‐balanced high‐level routing tree to route the aggregated data of CHs to the sink node. However, CC‐WMRT slightly has a better performance thanks to its low‐level routing strategy. As an advantage, the proposed schemes balance the energy consumption among different sensors. Numerical results show the efficiency of the CC‐TRT, CC‐MRT, and CC‐WMRT algorithms in terms of the number of transmissions, remaining energy, energy consumption variance, and network lifetime.     

LSAPSP: Load distribution‐based slot allocation and path establishment using optimized substance particle selection in sensor networks

Sensor node energy conservation is the primary design parameters in wireless sensor networks (WSNs). Energy efficiency in sensor networks directly prolongs the network lifetime. In the process of route discovery, each node cooperates to forward the data to the base station using multi‐hop routing. But, the nodes nearer to the base station are loaded more than the other nodes that lead to network portioning, packet loss and delay as a result nodes may completely loss its energy during the routing process. To rectify these issues, path establishment considers optimized substance particle selection, load distribution, and an efficient slot allocation scheme for data transmission between the sensor nodes in this paper. The selection of forwarders and conscious multi‐hop path is selected based on the route cost value that is derived directly by taking energy, node degree and distance as crucial metrics. Load distribution based slot allocation method ensures the balance of data traffic and residual energy of the node in areal‐time environment. The proposed LSAPSP simulation results show that our algorithm not only can balance the real‐time environment load and increase the network lifetime but also meet the needs of packet loss and delay.     

WCDS‐DCR: an energy‐efficient data‐centric routing scheme for wireless sensor networks

Wireless sensor networks (WSNs) typically consist of a large number of battery‐constrained sensors often deployed in harsh environments with little to no human control, thereby necessitating scalable and energy‐efficient techniques. This paper proposes a scalable and energy‐efficient routing scheme, called WCDS‐DCR, suitable for these WSNs. WCDS‐DCR is a fully distributed, data‐centric, routing technique that makes use of an underlying clustering structure induced by the construction of WCDS (Weakly Connected Dominating Set) to prolong network lifetime. It aims at extending network lifetime through the use of data aggregation (based on the elimination of redundant data packets) by some particular nodes. It also utilizes both the energy availability information and the distances (in number of hops) from sensors to the sink in order to make hop‐by‐hop, energy‐aware, routing decisions. Simulation results show that our solution is scalable, and outperforms existing schemes in terms of network lifetime. Copyright © 2010 John Wiley & Sons, Ltd.     

A multi‐agent self‐adaptative management framework

The self‐management vision, which has raised much interest in recent years, is only an operational aim that does not provide any solution in its definition on how to attain this management autonomy. The general contribution of this article suggests concepts, methods and mechanisms to conceive a self‐adaptative management framework, thus participating in this self‐management vision. This framework is composed of organizational aspects based on multi‐agent concepts, informational aspects based on different management ontologies and cooperative aspects based on specific agent behaviours which automate the accomplishment of management actions on the overall distributed environment. We have also implemented a prototype of this work to validate the feasibility of our approach and confirm the self‐adaptation capacities of the system. Copyright © 2008 John Wiley & Sons, Ltd.     

Network planning for mobile multi‐hop relay networks

In this paper, the coverage problem of network planning in mobile multi‐hop relay networks is defined on the basis of integer linear programming. In order to provide desired utilities and also meet deployment limitations for network planning, we propose a supergraph tree algorithm to place base stations and relay stations at the lowest cost position. Furthermore, another algorithm for avoiding the interference between base stations, which is called interference aware tree algorithm is also proposed. Both the proposed algorithms are formulated on the basis of a graph theoretic technique and analyzed in the simulation results. The results show that the supergraph tree algorithm provides the lowest construction cost with different network scenarios, and the interference aware tree algorithm provides the highest communication quality for mobile multi‐hop relay infrastructure‐based communication network planning. Copyright © 2013 John Wiley & Sons, Ltd.     

Two algorithms for multi‐constrained optimal multicast routing

Multimedia applications, such as video‐conferencing and video‐on‐demand, often require quality of service (QoS) guarantees from the network, typically in the form of minimum bandwidth, maximum delay, jitter and packet loss constraints, among others. The problem of multicast routing subject to various forms of QoS constraints has been studied extensively. However, most previous efforts have focused on special situations where a single or a pair of constraints is considered. In general, routing under multiple constraints, even in the unicast case is an NP‐complete problem. We present in this paper two practical and efficient algorithms, called multi‐constrained QoS dependent multicast routing (M_QDMR) and (multicasting routing with multi‐constrained optimal path selection (M_MCOP)), for QoS‐based multicast routing under multiple constraints with cost optimization. We provide proof in the paper that our algorithms are correct. Furthermore, through extensive simulations, we illustrate the effectiveness and efficiency of our proposals and demonstrate their significant performance improvement in creating multicast trees with lower cost and higher success probability. Copyright © 2003 John Wiley & Sons, Ltd.     

Toward energy‐proportional Internet core networks: an energy‐minimized routing and virtual topology design for Internet protocol layer

With the exponential growth of Internet traffic, the energy consumption issue of core networks is increasingly becoming critical. Today's core networks are highly underutilized most of the time because of the over‐provisioning and redundancy dimensioning, which results in severe energy inefficiency. In previous work, many non‐deterministic polynomial‐time hard mathematics formulation models have been proposed to minimize the energy consumption of core networks. However, effective heuristics are needed to solve these models in medium/large‐size networks. This work studies the energy‐minimized routing and virtual topology design problem of the power‐hungry Internet protocol (IP) layer in core networks, aiming to achieve an energy‐proportional IP layer by exploiting the variation of traffic with hours to reconfigure virtual topology and reroute traffic. We formulate energy‐minimized routing and virtual topology design as an Integer linear programming problem and propose a LR algorithm, a heuristic based on the Lagrangian relaxation, to solve this problem in a polynomial‐time. The simulation results indicate that the LR algorithm outperforms the best previous algorithm and can achieve a near energy‐proportional IP layer with significant power saving. Furthermore, a detailed analysis of simulation results is conducted, which suggests a design principle of network equipment to facilitate the power saving. Copyright © 2013 John Wiley & Sons, Ltd.     

A novel energy‐aware routing mechanism for SDN‐enabled WSAN

Energy consumption is one of the most important design constraints when building a wireless sensor and actuator network since each device in the network has a limited battery capacity, and prolonging the lifetime of the network depends on saving energy. Overcoming this challenge requires a smart and reconfigurable network energy management strategy. The Software‐Defined Networking (SDN) paradigm aims at building a flexible and dynamic network structure, especially in wireless sensor networks. In this study, we propose an SDN‐enabled wireless sensor and actuator network architecture that has a new routing discovery mechanism. To build a flexible and energy‐efficient network structure, a new routing decision approach that uses a fuzzy‐based Dijkstra's algorithm is developed in the study. The proposed architecture can change the existing path during data transmission, which is the key property of our model and is achieved through the adoption of the SDN approach. All the components and algorithms of the proposed system are modeled and simulated using the Riverbed Modeler software for more realistic performance evaluation. The results indicate that the proposed SDN‐enabled structure with fuzzy‐based Dijkstra's algorithm outperforms the one using the regular Dijkstra's and the ZigBee‐based counterpart, in terms of the energy consumption ratio, and the proposed architecture can provide an effective cluster routing while prolonging the network lifetime.     

Fixed channel assignment algorithm for multi‐radio multi‐channel MESH networks

Recently, multi‐radio mesh technology in wireless networks has been under extensive research. This is because of its potential of overcoming the inherent wireless multi‐hop throughput, scalability and latency problems caused by the half‐duplex nature of the IEEE 802.11. The concept of deploying multiple radios in wireless network access points (APs) has shown a promising way to enhance the channel selection and the route formation while the MESH topology allows more fine‐grained interference management and topology control. Within this realm, given a set of end‐to‐end objectives, there are multiple issues that need to be identified when we consider the optimization problem for fixed multi‐channel multi‐hop wireless networks with multiple radios. This paper addresses the static channel assignment problem for multichannel multi‐radio static wireless mesh networks. We first discuss its similarities and differences with the channel assignment problem in cellular networks (WMN). Next, we present four metrics based on which mesh channel assignments can be obtained. Three of these metrics attempt to maximize simultaneous transmissions in a mesh network, either directly or indirectly. The fourth metric quantifies the ‘diversity’ of a particular assignment and can be used as a secondary criterion to the other three metrics. Related optimization models have also been developed. Copyright © 2007 John Wiley & Sons, Ltd.     

Utility‐optimal cross‐layer resource allocation in distributed wireless cooperative networks

In this paper, we propose a distributed cross‐layer resource allocation algorithm for wireless cooperative networks based on a network utility maximization framework. The algorithm provides solutions to relay selections, flow pass probabilities, transmit rate, and power levels jointly with optimal congestion control and power control through balancing link and physical layers such that the network‐wide utility is optimized. Via dual decomposition and subgradient method, we solve the utility‐optimal resource allocation problem by subproblems in different layers of the protocol stack. Furthermore, by introducing a concept of pseudochannel gain, we model both the primal direct logical link and its corresponding cooperative transmission link as a single virtual direct logical link to simplify our network utility framework. Eventually, the algorithm determines its primal resource allocation levels by employing reverse‐engineering of the pseudochannel gain model. Numerical experiments show that the convergence of the proposed algorithm can be obtained and the performance of the optimized network can be improved significantly. Copyright © 2012 John Wiley & Sons, Ltd.     

Two‐sided matching framework for optimal user association in 5G multi‐RAT UDNs

Recently, academic and industrial research communities are paying more explicit attention to the 5G multiple radio access technology ultra‐dense networks (5G multi‐RAT UDNs) for boosting network capacity, especially in UD urban zones. To this aim, in this paper, we intend to tackle the user association problem in 5G multi‐RAT UDNs. By considering the decoupled uplink/downlink access (DUDA), we divide our user association problem into two distinct subproblems representing, respectively, the uplink and the downlink channels. Next, we formulated each one as a nonlinear optimization problem with binary variables. Then, to solve them, we were restricted by the hard complexity, as well as the hard feasibility of centralized user association schemes. Thus, to resolve our user association problem in a reasonable time and distributed manner, we formulated each subproblem as a many‐to‐one matching game based on matching theory. Next, we provide two fully distributed association algorithms to compute the uplink and downlink stable matching among user equipments (UEs) and base stations (BSs). Simulation results corroborate our theoretical model and show the effectiveness and improvement of our achieved results in terms of the overall network performance, quality of service (QoS), and energy efficiency (EE) of UEs.