Optimizing the throughput‐lifetime tradeoff in wireless sensor networks with link scheduling,rate adaptation,and power control

Throughput and lifetime are usually conflicting objectives in designing wireless sensor networks; hence, the right balance needs to be found. With this aim in view, we address in this paper the problem of minimizing the frame length defined within a time division multiple access scheme and the problem of maximizing network lifetime subject to a maximum frame length. The pursued solution in either case leverages a wide range of parameters related to coverage, routing, transmission power, and data rate. Furthermore, it is consistent with the physical interference model. To this end, we rely on column generation technique to derive near‐optimal solutions even when the integrality constraints on coverage and flow variables are enforced. Moreover, we propose a polynomial‐time heuristic algorithm to solve efficiently the underlying NP‐hard problem of concurrent link selection with discrete power control and rate adaptation. Simulation results show that our heuristic algorithm leads to solutions within 3% of optimality while saving around 99% of computation time. Besides, the results illustrate the significant impact of power control and rate adaptation on throughput and lifetime improvement. Interestingly, we found that network lifetime can be significantly prolonged when traffic demands are sufficiently low at the affordable cost of small decrease in throughput. Copyright © 2015 John Wiley & Sons, Ltd.     

基于ERPMT改进启发式方法的WSN寿命最大化算法

针对传感器节点的电池容量限制导致无线传感网络寿命低的问题,基于容量最大化(CMAX)、线上最大化寿命(OML)两种启发式方法以及高效路由能量管理技术(ERPMT),提出了基于ERPMT改进启发式方法的无线传感网络寿命最大化算法。首先,通过启发式方法初始化每个传感器节点,将节点能量划分为传感器节点起源数据和其它节点数据延迟;然后利用加入的一种优先度量延迟一跳节点的能量消耗;最后,根据路径平均能量为每个路由分配一个优先级,并通过ERPMT实现最终的无线传感网络优化。针对不同分布类型网络寿命的实验验证了本文算法的有效性及可靠性,实验结果表明,相比较为先进的启发式方法CMAX及OML,本文算法明显增大了无线传感网络的覆盖范围,并且大大地延长了网络的寿命。     

Range‐free intersecting chord‐based geometric localization scheme for wireless sensor networks

Recent advancement in wireless sensor network has contributed greatly to the emerging of low‐cost, low‐powered sensor nodes. Even though deployment of large‐scale wireless sensor network became easier, as the power consumption rate of individual sensor nodes is restricted to prolong the battery lifetime of sensor nodes, hence the heavy computation capability is also restricted. Localization of an individual sensor node in a large‐scale geographic area is an integral part of collecting information captured by the sensor network. The Global Positioning System (GPS) is one of the most popular methods of localization of mobile terminals; however, the use of this technology in wireless sensor node greatly depletes battery life. Therefore, a novel idea is coined to use few GPS‐enabled sensor nodes, also known as anchor nodes, in the wireless sensor network in a well‐distributed manner. Distances between anchor nodes are measured, and various localization techniques utilize this information. A novel localization scheme Intersecting Chord‐Based Geometric Localization Scheme (ICBGLS) is proposed here, which loosely follows geometric constraint‐based algorithm. Simulation of the proposed scheme is carried out for various communication ranges, beacon broadcasting interval, and anchor node traversal techniques using Omnet++ framework along with INET framework. The performance of the proposed algorithm (ICBGLS), Ssu scheme, Xiao scheme, and Geometric Constraint‐Based (GCB) scheme is evaluated, and the result shows the fact that the proposed algorithm outperforms the existing localization algorithms in terms of average localization error. The proposed algorithm is executed in a real‐time indoor environment using Arduino Uno R3 and shows a significant reduction in average localization time than GCB scheme and similar to that of the SSU scheme and Xiao scheme.     

A coordinated multi‐point‐based quality of service provision resource allocation scheme with inter‐cell interference mitigation

The paper investigates resource allocation via power control for inter‐cell interference (ICI) mitigation in an orthogonal frequency division multiple access‐based cellular network. The proposed scheme is featured by a novel subcarrier assignment mechanism at a central controller for ICI, which is further incorporated with an intelligent power control scheme. We formulate the system optimization task into a constrained optimization problem for maximizing accepted users' requirements. To improve the computation efficiency, a fast yet effective heuristic approach is introduced for divide and conquer. Simulation results demonstrate that the proposed resource allocation scheme can significantly improve the network capacity compared with a common approach by frequency reuse. Copyright © 2014 John Wiley & Sons, Ltd.     

DynaChannAl: dynamic channel allocation with minimal end‐to‐end delay for two‐tier wireless sensor networks

With recent advances in wireless networking and in low‐power sensor technology, wireless sensor networks (WSNs) have taken significant roles in various applications. Whereas some WSNs only require minimal bandwidth, newer applications operate with a noticeably larger amount of data. One way to deal with these applications is to maximize the available capacity by utilizing multiple wireless channels. We propose DynaChannAl, a distributed dynamic wireless channel allocation algorithm that effectively distributes nodes to multiple wireless channels in WSNs. Specifically, DynaChannAl targets applications where mobile nodes connect to preexisting wireless backbones and takes the expected end‐to‐end queuing delay as its core metric. We used the link quality indicator values provided by 802.15.4 radios to whitelist high‐quality links and evaluate these links with the aggregated queuing latency, making it useful for applications that require minimal end‐to‐end delay (i.e., health care). DynaChannAl is a lightweight and adoptable scheme that can be incorporated easily with predeveloped systems. As the first study to consider end‐to‐end latency as the core metric for channel allocation in WSNs, we evaluate DynaChannAl on a 45 node test bed and show that DynaChannAl successfully distributes source nodes to different channels and enables them to select channels and links that minimizes the end‐to‐end latency. Copyright © 2012 John Wiley & Sons, Ltd.     

Energy‐efficient resource allocation for lifetime maximization in M2M networks

Machine‐to‐machine (M2M) communications is one of the major enabling technologies for the realization of the Internet of Things (IoT). Most machine‐type communication devices (MTCDs) are battery powered, and the battery lifetime of these devices significantly affects the overall performance of the network and the quality of service (QoS) of the M2M applications. This paper proposes a lifetime‐aware resource allocation algorithm as a convex optimization problem for M2M communications in the uplink of a single carrier frequency division multiple access (SC‐FDMA)‐based heterogeneous network. A K‐means clustering is introduced to reduce energy consumption in the network and mitigate interference from MTCDs in neighbouring clusters. The maximum number of clusters is determined using the elbow method. The lifetime maximization problem is formulated as a joint power and resource block maximization problem, which is then solved using Lagrangian dual method. Finally, numerical simulations in MATLAB are performed to evaluate the performance of the proposed algorithm, and the results are compared to existing heuristic algorithm and inbuilt MATLAB optimal algorithm. The simulation results show that the proposed algorithm outperforms the heuristic algorithm and closely model the optimal algorithm with an acceptable level of complexity. The proposed algorithm offers significant improvements in the energy efficiency and network lifetime, as well as a faster convergence and lower computational complexity.     

QoS‐aware target coverage in wireless sensor networks

Wireless sensor networks have emerged recently as an effective way of monitoring remote or inhospitable physical targets, which usually have different quality of service (QoS) constraints, i.e., different targets may need different sensing quality in terms of the number of transducers, sampling rate, etc. In this paper, we address the problem of optimizing network lifetime while capturing those diversified QoS coverage constraints in such surveillance sensor networks. We show that this problem belongs to NP‐complete class. We define a subset of sensors meeting QoS requirements as a coverage pattern, and if the full set of coverage patterns is given, we can mathematically formulate the problem. Directly solving this formulation however is difficult since number of coverage patterns may be exponential to number of sensors and targets. Hence, a column generation (CG)‐based approach is proposed to decompose the original formulation into two subproblems and solve them iteratively. Here a column corresponds to a feasible coverage pattern, and the idea is to find a column with steepest ascent in lifetime, based on which we iteratively search for the maximum lifetime solution. An initial feasible set of patterns is generated through a novel random selection algorithm (RSA), in order to launch our approach. Experimental data demonstrate that the proposed CG‐based approach is an efficient solution, even in a harsh environment. Simulation results also reveal the impact of different network parameters on network lifetime, giving certain guidance on designing and maintaining such surveillance sensor networks. Copyright © 2009 John Wiley & Sons, Ltd.     

QoS‐aware routing and power control algorithm for multimedia service over multi‐hop mobile ad hoc network

This paper presents a QoS (quality of service) aware routing and power control algorithm consuming low transmission power for multimedia service over mobile ad hoc network. Generally, multimedia services need stringent QoS over the network. However, it is not easy to guarantee the QoS over mobile ad hoc network since its network resources are very limited and time‐varying. Furthermore, only a limited amount of power is available at mobile nodes, which makes the problem more challenging. We propose an effective routing and power control algorithm for multimedia services that satisfies end‐to‐end delay constraint with low transmission power consumption. The proposed algorithm supports the required bandwidth by controlling each link channel quality over route in a tolerable range. In addition, a simple but effective route maintenance mechanism is implemented to avoid link failures that may significantly degrade streaming video quality. Finally, performance comparison with existing algorithms is presented in respect to traditional routing performance metrics, and an achievable video quality comparison is provided to demonstrate the superiority of the proposed algorithm for multimedia services over mobile ad hoc network. Copyright © 2010 John Wiley & Sons, Ltd.     

DRP: An energy‐efficient routing protocol for underwater sensor networks

The features of transmissions in underwater sensor networks (UWSNs) include lower transmission rate, longer delay time, and higher power consumption when compared with terrestrial radio transmissions. The negative effects of transmission collisions deteriorate in such environments. Existing UWSN routing protocols do not consider the transmission collision probability differences resulting from different transmission distances. In this paper, we show that collision probability plays an important role in route selection and propose an energy‐efficient routing protocol (DRP), which considers the distance‐varied collision probability as well as each node's residual energy. Considering these 2 issues, DRP can find a path with high successful transmission rate and high‐residual energy. In fact, DRP can find the path producing the longest network lifetime, which we have confirmed through theoretical analysis. To the best of our knowledge, DRP is the first UWSN routing protocol that uses transmission collision probability as a factor in route selection. Simulation results verify that DRP extends network lifetime, increases network throughput, and reduces end‐to‐end delay when compared with solutions without considering distance‐varied collision probability or residual energy.     

Power‐efficient routing for SDN with discrete link rates and size‐limited flow tables: A tree‐based particle swarm optimization approach

Software‐defined networking is a promising networking paradigm for achieving programmability and centralized control in communication networks. These features simplify network management and enable innovation in network applications and services such as routing, virtual machine migration, load balancing, security, access control, and traffic engineering. The routing application can be optimized for power efficiency by routing flows and coalescing them such that the least number of links is activated with the lowest link rates. However, in practice, flow coalescing can generally overflow the flow tables, which are implemented in a size‐limited and power‐hungry ternary content addressable memory (TCAM). In this paper, a set of practical constraints is imposed to the software‐defined networking routing problem, namely, size‐limited flow table and discrete link rate constraints, to ensure applicability in real networks. Because the problem is NP‐hard and difficult to approximate, a low‐complexity particle swarm optimization–based and power‐efficient routing (PSOPR) heuristic is proposed. Performance evaluation results revealed that PSOPR achieves more than 90% of the optimal network power consumption while requiring only 0.0045% to 0.9% of the optimal computation time in real‐network topologies. In addition, PSOPR generates shorter routes than the optimal routes generated by CPLEX.     

Design of energy‐efficient cloud systems via network and resource virtualization

Data centers play a crucial role in the delivery of cloud services by enabling on‐demand access to the shared resources such as software, platform and infrastructure. Virtual machine (VM) allocation is one of the challenging tasks in data center management since user requirements, typically expressed as service‐level agreements, have to be met with the minimum operational expenditure. Despite their huge processing and storage facilities, data centers are among the major contributors to greenhouse gas emissions of IT services. In this paper, we propose a holistic approach for a large‐scale cloud system where the cloud services are provisioned by several data centers interconnected over the backbone network. Leveraging the possibility to virtualize the backbone topology in order to bypass IP routers, which are major power consumers in the core network, we propose a mixed integer linear programming (MILP) formulation for VM placement that aims at minimizing both power consumption at the virtualized backbone network and resource usage inside data centers. Since the general holistic MILP formulation requires heavy and long‐running computations, we partition the problem into two sub‐problems, namely, intra and inter‐data center VM placement. In addition, for the inter‐data center VM placement, we also propose a heuristic to solve the virtualized backbone topology reconfiguration computation in reasonable time. We thoroughly assessed the performance of our proposed solution, comparing it with another notable MILP proposal in the literature; collected experimental results show the benefit of the proposed management scheme in terms of power consumption, resource utilization and fairness for medium size data centers. Copyright © 2013 John Wiley & Sons, Ltd.     

Energy‐efficient power control for uplink spectrum‐sharing heterogeneous networks

This article considers energy‐efficient power control schemes for interference management in uplink spectrum‐sharing heterogeneous networks that maximize the energy efficiency of users, protect the macro base station, and support users with QoS consideration. In the first scenario, we define the objective function as the weighted sum of the energy efficiencies and develop an efficient global optimization algorithm with global linear and local quadratic rate of convergence to solve the considered problem. To ensure fairness among individual user equipments (UEs) in terms of energy efficiency, we consider the max‐min problem, where the objective is defined as the weighted minimum of the energy efficiencies, and a fractional programming theory and the dual decomposition method are jointly used to solve the problem and investigate an iterative algorithm. As by‐products, we further discuss the global energy efficiency problem and consider near‐optimal schemes. Numerical examples are provided to demonstrate significant improvements of the proposed algorithms over existing interference management schemes.     

Optimal Amplify‐and‐Forward Scheme for Parallel Relay Networks with Correlated Relay Noise

This paper studies a parallel relay network where the relays employ an amplify‐and‐forward (AF) relaying scheme and are subjected to individual power constraints. We consider correlated effective relay noise arising from practical scenarios when the relays are exposed to common interferers. Assuming that the noise covariance and the full channel state information are available, we investigate the problem of finding the optimal AF scheme in terms of maximum end‐to‐end transmission rate. It is shown that the maximization problem can be equivalently transformed to a convex semi‐definite program, which can be efficiently solved. Then an upper bound on the maximum achievable AF rate of this network is provided to further evaluate the performance of the optimal AF scheme. It is proved that the upper bound can be asymptotically achieved in two special regimes when the transmit power of the source node or the relays is sufficiently large. Finally, both theoretical and numerical results are given to show that, on average, noise correlation is beneficial to the transmission rate — whether the relays know the noise covariance matrix or not.     

A lightweight authentication scheme based on self‐updating strategy for space information network

The security of space information network (SIN) is getting more and more important now. Because of the special features of SIN (e.g., the dynamic and unstable topology, the highly exposed links, the restricted computation power, the flexible networking methods, and so on), the security protocol for SIN should have a balance between security properties and computation/storage overhead. Although a lot of security protocols have been proposed recently, few can provide overall attacks resistance power with low computation and storage cost. To solve this problem, in this paper we propose a lightweight authentication scheme for space information network. It is mainly based on the self‐updating strategy for user's temporary identity. The scheme consists of two phases, namely, the registration phase and the authentication phase. All the computing operations involved are just hash function (h), the bit‐wise exclusive‐or operation (⊕), and the string concatenation operation (||), which are of low computation cost. The security properties discussion and the attacks–resistance power analysis show that the proposed authentication scheme can defend against various typical attacks, especially denial of service attacks. It is sufficiently secure with the lowest computation and storage costs. Furthermore, the formal security proof in SVO logic also demonstrates that the scheme can satisfy the security goals very well. Copyright © 2016 John Wiley & Sons, Ltd.     

Gossip‐based scalable directed diffusion for wireless sensor networks

Directed diffusion (DD) is a promising data‐centric routing scheme for wireless sensor networks (WSNs). But the heavy flooding overhead involved in interest propagation causes scalability issues when DD is applied in large scale, interactive and dynamically changing sensor networks. To solve this problem, we propose a scalable version of DD called gossip‐based scalable directed diffusion (GSDD) in this paper. GSDD uses the same routing framework as DD but integrates gossiping in interest propagation and employs dynamic regional gossiping in path exploration phase to reduce the flooding overhead. Our analysis and simulation results demonstrate that GSDD is able to reduce the data delivery cost of DD by up to 25%; thus, significantly reduce energy consumption and prolong the lifetime of sensor nodes. Therefore, GSDD overcomes the scalability problem of DD and is suitable for large‐scale WSNs. Copyright © 2011 John Wiley & Sons, Ltd.     

Lifetime optimization for reliable broadcast and multicast in wireless ad hoc networks

In this paper, we consider the reliable broadcast and multicast lifetime maximization problems in energy‐constrained wireless ad hoc networks, such as wireless sensor networks for environment monitoring and wireless ad hoc networks consisting of laptops or PDAs with limited battery capacities. In packet loss‐free networks, the optimal solution of lifetime maximization problem can be easily obtained by tree‐based algorithms. In unreliable networks, we formulate them as min–max tree problems and prove them NP‐complete by a reduction from a well‐known minimum degree spanning tree problem. A link quality‐aware heuristic algorithm called Maximum Lifetime Reliable Broadcast Tree (MLRBT) is proposed to build a broadcast tree that maximizes the network lifetime. The reliable multicast lifetime maximization problem can be solved as well by pruning the broadcast tree produced by the MLRBT algorithm. The time complexity analysis of both algorithms is also provided. Simulation results show that the proposed algorithms can significantly increase the network lifetime compared with the traditional algorithms under various distributions of error probability on lossy wireless links. Copyright © 2012 John Wiley & Sons, Ltd.     

On the Planning of Wireless Sensor Networks: Energy-Efficient Clustering under the Joint Routing and Coverage Constraint

Minimizing energy dissipation and maximizing network lifetime are important issues in the design of applications and protocols for sensor networks. Energy-efficient sensor state planning consists in finding an optimal assignment of states to sensors in order to maximize network lifetime. For example, in area surveillance applications, only an optimal subset of sensors that fully covers the monitored area can be switched on while the other sensors are turned off. In this paper, we address the optimal planning of sensors' states in cluster-based sensor networks. Typically, any sensor can be turned on, turned off, or promoted cluster head, and a different power consumption level is associated with each of these states. We seek an energy-optimal topology that maximizes network lifetime while ensuring simultaneously full area coverage and sensor connectivity to cluster heads, which are constrained to form a spanning tree used as a routing topology. First, we formulate this problem as an Integer Linear Programming model that we prove NP-Complete. Then, we implement a Tabu search heuristic to tackle the exponentially increasing computation time of the exact resolution. Experimental results show that the proposed heuristic provides near-optimal network lifetime values within low computation times, which is, in practice, suitable for large-sized sensor networks.     

Optimal scheduling of coordinated multipoint transmissions in cellular networks

In this paper, we study the optimal scheduling problem in coordinated multipoint (CoMP) transmission–based cellular networks. We consider joint transmission and coordinated scheduling together in CoMP transmission–based cellular networks and develop an optimization framework to compute the optimal max‐min throughput and the optimal scheduling of the transmissions to the users. The optimization problem is found to be a complex linear program with number of variables in for a cellular network of N users and K cells. We solve the optimization problem for several network instances using an optimization tool. The numerical results show that the optimal CoMP transmission provides a significant throughput gain over a traditional transmission. We find that in optimal scheduling the fraction time of coordinated scheduling is higher than that of joint transmission. To solve the optimization problem without any optimization tool, we propose a heuristic algorithm. The performance of the heuristic algorithm is evaluated and found to be provided throughput around 97% of the optimal throughput. Further, we extend the optimization framework to study joint scheduling and power allocation (JSPA) problem in CoMP transmission–based cellular networks. We numerically solve the JSPA problem for the network instances and demonstrate that the optimal power allocation at the base stations is not binary for a significant fraction of time of scheduling. However, the gain in max‐min throughput by the optimal JSPA technique over the optimal scheduling technique is not significant.     

Clustering‐based low‐complexity resource allocation in two‐tier femtocell networks with QoS provisioning

In this paper, we study the resource allocation problem of the uplink transmission with delay quality‐of‐service constraints in two‐tier femtocell networks. Particularly, to provide statistical delay guarantees, the effective capacity is employed as the network performance measure instead of the conventional Shannon capacity. To make the problem computationally efficient and numerically tractable, we decompose the problem into three subproblems, namely, cluster configuration subproblem, intra‐cluster subchannel allocation subproblem and inter‐cluster power control subproblem. Firstly, we develop a low‐complexity heuristic semi‐dynamic clustering scheme, where the delay of the channel state information feedback via backhaul is considered. We model such system in the framework of networked partial observation Markov decision process and derive a strategy to reduce the search range for the best cluster configuration. Then, for a given cluster configuration, the cluster heads deal with subchannel allocation and power control within each cluster. We propose a subchannel allocation scheme with proportional fairness. Thereafter, the inter‐cluster power control subproblem is modeled as a set of exact potential games, and a channel quality related pricing mechanism is presented to mitigate inter‐cluster interference. The existence and uniqueness of Nash equilibriums for the proposed game are investigated, and an effective decentralized algorithm with guaranteed convergence is designed. Simulation results demonstrate that the proposed algorithms not only have much lower computational complexity but also perform close to the exhaustive search solutions and other existing schemes. Copyright © 2015 John Wiley & Sons, Ltd.     

Energy‐aware virtual multi‐input‐multi‐output‐based routing for wireless ad hoc networks

Virtual multi‐input‐multi‐output (vMIMO) technology is becoming a promising way to improve the energy efficiency of wireless networks. Previous research always builds up the vMIMO‐based routing on the fixed structure such as clusters, and the MIMO mode is omitted in most cases. So, they cannot fully explore the advantage of vMIMO in routing. In this paper, we study a general routing scheme in which no fixed structure is required, and any communication mode of vMIMO is allowed for sake of the energy efficiency. We define two vMIMO‐based routing problems aiming to energy‐minimization and lifetime‐optimization. The first problem can be solved by our distributed energy‐minimum vMIMO‐based algorithm. The algorithm constructs the virtual cooperative graph, and applies the shortest path method on the virtual cooperative graph to solve this problem. The second problem is non‐deterministic polynomial‐time hard, and we design the distributed lifetime‐oriented vMIMO‐based algorithm, which is based on the modified Bellman‐Ford method. It can reach approximation ratio of four. The simulations show that our algorithms can work well in many situations. For example, distributed lifetime‐oriented vMIMO‐based algorithm can prolong the lifetime about 20.2% in dense topologies compared with the cooperative routing algorithm on average. Copyright © 2015 John Wiley & Sons, Ltd.