CAKA: a novel cache‐aware K‐anycast routing scheme for publish/subscribe‐based information‐centric network

In the past few years, many publish/subscribe‐based information‐centric network (PS‐ICN) architectures have been proposed and investigated to efficiently deliver information from content publishers to subscribers. However, most existing studies on PS‐ICN have not considered how to utilize in‐network caches, which is a common but important feature in ICN. To address this issue, in this paper, we propose a novel cache‐aware K‐anycast routing scheme, namely, CAKA, that can significantly improve the performance of content delivery. Specifically, we choose PURSUIT, which is one of the most important PS‐ICN architectures, and leverage its bidirectional communication procedure to do the following: (1) enable multiple publishers to send probing messages to the same subscriber; and (2) allow the subscriber to retrieve content objects using K‐anycast routing and network coding. In this study, we extend the PURSUIT protocol to support cache‐aware K‐anycast routing and design the algorithms to choose multiple partially disjointed paths for probing, and to select paths for content retrieval. To evaluate the performance of the proposed scheme, we develop not only a simulation testbed, but also a prototype running in a realistic network environment. Our studies show that the proposed scheme can significantly reduce the average hops to retrieve content objects, with very small overheads. Copyright © 2015 John Wiley & Sons, Ltd.     

Energy‐efficient multi‐level and distance‐aware clustering mechanism for WSNs

Most sensor networks are deployed at hostile environments to sense and gather specific information. As sensor nodes have battery constraints, therefore, the research community is trying to propose energy‐efficient solutions for wireless sensor networks (WSNs) to prolong the lifetime of the network. In this paper, we propose an energy‐efficient multi‐level and distance‐aware clustering (EEMDC) mechanism for WSNs. In this mechanism, the area of the network is divided into three logical layers, which depends upon the hop‐count‐based distance from the base station. The simulation outcomes show that EEMDC is more energy efficient than other existing conventional approaches. Copyright © 2013 John Wiley & Sons, Ltd.     

Energy‐aware geographic routing in wireless sensor networks with anchor nodes

Energy efficiency has become an important design consideration in geographic routing protocols for wireless sensor networks because the sensor nodes are energy constrained and battery recharging is usually not feasible. However, numerous existing energy‐aware geographic routing protocols are energy‐inefficient when the detouring mode is involved in the routing. Furthermore, most of them rarely or at most implicitly take into account the energy efficiency in the advance. In this paper, we present a novel energy‐aware geographic routing (EAGR) protocol that attempts to minimize the energy consumption for end‐to‐end data delivery. EAGR adaptively uses an existing geographic routing protocol to find an anchor list based on the projection distance of nodes for guiding packet forwarding. Each node holding the message utilizes geographic information, the characteristics of energy consumption, and the metric of advanced energy cost to make forwarding decisions, and dynamically adjusts its transmission power to just reach the selected node. Simulation results demonstrate that our scheme exhibits higher energy efficiency, smaller end‐to‐end delay, and better packet delivery ratio compared to other geographic routing protocols. Copyright © 2011 John Wiley & Sons, Ltd.     

Energy‐aware supply route data collecting methods using wireless sensor networks

In military action, marching is a common method used for supply‐troop movement. Supply routes are typically in the wilderness where the route conditions change over time. This paper proposes a power‐saving algorithm allowing supply troops to collect route information using wireless sensor network technology. Each member in the marching supply troop is equipped with a battery‐powered sensor. To save power consumption, the proposed methods schedule the sleeping period for each member according to the size of the marching supply troop and its moving velocity. Two data carrying methods are proposed to reduce the frequency of long‐distance data uploading. The first method allows the uploaded data to be carried within a single‐round data collection period, and the second method extends the data carrying period to multiple rounds. The simulation results show that scheduling a sleep period can prolong the sensing distance along the route. These two proposed methods can add an additional 18–70% in distance data over methods without scheduling a sleep period. The energy spent on long‐distance data transmissions can be improved by 7–25%. Copyright © 2015 John Wiley & Sons, Ltd.     

Improving MANET performance by a hop‐aware and energy‐based buffer management scheme

A hop‐aware and energy‐based buffer management scheme (HEB) is proposed in this paper. HEB can provide better quality of service to packets with real‐time requirements and improve MANET power efficiency. In our algorithm, the buffer is divided into real‐time and non‐real‐time partitions. We consider the number of hops passed, the power levels of the transmitting node, the predicted number of remaining hops, and waiting time in the buffer to determine packet transmission priority. In addition, specialized queue management and a probabilistic scheduling algorithm are proposed to decrease retransmissions caused by packet losses. Mathematical derivations of loss rates and end‐to‐end delays are also proposed. Coincidence between mathematical and simulation results is also shown. Finally, the HEB is compared with first in first out, random early detection, and hop‐aware buffering scheme. Simulation results show that the proposed algorithm reduces loss rates, power consumption, and end‐to‐end delays for real‐time traffic, considerably improving the efficiency of queue management in MANET. Copyright © 2012 John Wiley & Sons, Ltd.     

Energy‐efficient device‐to‐device communication using adaptive resource‐block allocation

Device‐to‐device (D2D) communication in the fifth‐generation (5G) wireless communication networks (WCNs) reuses the cellular spectrum to communicate over the direct links and offers significant performance benefits. Since the scarce radio spectrum is the most precious resource for the mobile‐network operators (MNOs), optimizing the resource allocation in WCNs is a major challenge. This paper proposes an adaptive resource‐block (RB) allocation scheme for adequate RB availability to every D2D pair in a trisectored cell of the 5G WCN. The hidden Markov model (HMM) is used to allocate RBs adaptively, promoting high resource efficiency. The stringent quality‐of‐service (QoS) and quality‐of‐experience (QoE) requirements of the evolutionary 5G WCNs must not surpass the transmission power levels. This is also addressed while using HMM for RB allocation. Thus, an energy‐efficient RB allocation is performed, with higher access rate and mean opinion score (MOS). Cell sectoring effectively manages the interference in the 5G networks amid ultrauser density. The potency of the proposed adaptive scheme has been verified through simulations. The proposed scheme is an essential approach to green communication in 5G WCNs.     

Real‐time performance evaluation of asynchronous time division traffic‐aware and delay‐tolerant scheme in ad hoc sensor networks

Wireless infrastructureless networks demand high resource availability with respect to the progressively decreasing energy consumption. A variety of new applications with different service requirements demand fairness to the service provision and classification, and reliability in an end‐to‐end manner. High‐priority packets are delivered within a hard time delay bound whereas improper power management in wireless networks can substantially degrade the throughput and increase the overall energy consumed. In this work a new scheme is being proposed and evaluated in real time using a state‐based layered oriented architecture for energy conservation (EC). The proposed scheme uses the node's self‐tuning scheme, where each node is assigned with a dissimilar sleep and wake time, based on traffic that is destined for each node. This approach is based on stream's characteristics with respect to different caching behavioral and storage‐capacity characteristics, and considers a model concerning the layered connectivity characteristics for enabling the EC mechanism. EC characteristics are modeled and through the designed tiered architecture the estimated metrics of the scheme can be bounded and tuned into certain regulated values. The real‐time evaluation results were extracted by using dynamically moving and statically located sensor nodes. A performance comparison is done with respect to different data traffic priority classifications following a real‐time asymmetrical transmission channel. Results have shown the scheme's efficiency in conserving energy while the topology configuration changes with time. Copyright © 2009 John Wiley & Sons, Ltd.     

e‐LiteSense: Self‐adaptive energy‐aware data sensing in WSN environments

Currently deployed in a wide variety of applicational scenarios, wireless sensor networks (WSNs) are typically a resource‐constrained infrastructure. Consequently, characteristics such as WSN adaptability, low‐overhead, and low‐energy consumption are particularly relevant in dynamic and autonomous sensing environments where the measuring requirements change and human intervention is not viable. To tackle this issue, this article proposes e‐LiteSense as an adaptive, energy‐aware sensing solution for WSNs, capable of auto‐regulate how data are sensed, adjusting it to each applicational scenario. The proposed adaptive scheme is able to maintain the sensing accuracy of the physical phenomena, while reducing the overall process overhead. In this way, the adaptive algorithm relies on low‐complexity rules to establish the sensing frequency weighting the recent drifts of the physical parameter and the levels of remaining energy in the sensor. Using datasets from WSN operational scenarios, we prove e‐LiteSense effectiveness in self‐regulating data sensing accurately through a low‐overhead process where the WSN energy levels are preserved. This constitutes a step‐forward for implementing self‐adaptive energy‐aware data sensing in dynamic WSN environments.     

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.     

Performance optimization of duty‐cycled MAC in delay‐energy constrained sensor network under uniform and nonuniform traffic generation

Duty‐cycle at the media access control (MAC) layer plays a key role in energy savings and network lifetime extension. It consists in putting a node's radio in the sleep state as soon as it has no communication activity. Traditional wireless sensor network MAC protocols are designed with short duty‐cycles at the cost of long delays. Careful design is required for joint energy‐delay constrained applications, where the optimal parameters should be thoroughly derived. The present paper deals with this issue and mathematically derives optimal values of key MAC parameters under low data rate applications for 3 well‐known duty‐cycled MAC protocols, WiseMAC, SCP‐MAC, and LMAC as representatives of 3 MAC protocol categories, respectively, preamble‐sampling, slotted contention‐based, and frame‐based. The analysis provides also the optimum traffic sampling rate that guarantees the minimum energy consumption. It shows the role of these parameters in achieving the targeted end‐to‐end delay constraints under network models with uniform traffic generation, for ring and grid topologies. As a second contribution, the model is extended to nonuniform traffic scenarios, where a certain percentage of deployed nodes are relays whose role is to balance traffic forwarding and save the overall network energy. The results reveal that different optimal internal MAC parameters and traffic generation rates can be found for different configurations of relay nodes deployment, which achieve minimal network energy consumption while satisfying the application required end‐to‐end delay threshold.     

A zone co‐operation approach for efficient caching in mobile ad hoc networks

Mobile Ad hoc NETwork (MANET) presents a constrained communication environment due to fundamental limitations of client resources, insufficient wireless bandwidth and users' frequent mobility. Caching of frequently accessed data in such environment is a potential technique that can improve the data access performance and availability. Co‐operative caching, which allows the sharing and co‐ordination of cached data among clients, can further explore the potential of the caching techniques. In this paper, we propose a novel scheme, called zone co‐operative (ZC) for caching in MANETs. In ZC scheme, one‐hop neighbours of a mobile client form a co‐operative cache zone. For a data miss in the local cache, each client first searches the data in its zone before forwarding the request to the next client that lies along routing path towards server. As a part of cache management, cache admission control and value‐based replacement policy are developed to improve the data accessibility and reduce the local cache miss ratio. An analytical study of ZC based on data popularity, node density and transmission range is also performed. Simulation experiments show that the ZC caching mechanism achieves significant improvements in cache hit ratio and average query latency in comparison with other caching strategies. Copyright © 2006 John Wiley & Sons, Ltd.     

Minimum spanning tree–based delay‐aware mobile sink traversal in wireless sensor networks

Energy efficient data collection in a delay‐bound application is a challenging issue for mobile sink–based wireless sensor networks. Many researchers have proposed the concept of rendezvous points (RPs) to design the path for the mobile sink. Rendezvous points are the locations in the network where the mobile sink halts and collects data from the nearby sensor nodes. However, the selection of RPs for the design of path has a significant impact on timely data collection from the network. In this paper, we propose an efficient algorithm for selection of the RPs for efficient design of mobile sink trajectory in delay‐bound applications of wireless sensor networks. The algorithm is based on a virtual path and minimum spanning tree and shown to maximize network lifetime. We perform extensive simulations on the proposed algorithm and compare results with the existing algorithms to demonstrate the efficiency of the proposed algorithm of various performance metrics.     

Energy‐aware dynamic task offloading and collective task execution in mobile cloud computing

There is a good opportunity for enlightening the services of the mobile devices by introducing computational offloading using cloud technology. Offloading is a process for managing the complexity of the mobile environment by migrating computational load to the cloud. The mobile devices oblige the quick response for the offloading requests; it is dependent on network connectivity. The cloud services take long set‐up time irrespective of network connectivity. In this paper, new system architecture for the dynamic task offloading in the mobile cloud environment is proposed. The architecture includes the offloading algorithm that concentrates on energy consumption of the tasks both in the local and remote environment. The proposed algorithm formulates a collective task execution model for minimizing the energy consumption. The architecture concentrates on the network model by considering the task completion time in three different network scenarios. The experimental results show the efficiency of the suggested architecture in reducing the energy consumption and completion time of the tasks.     

Congestion‐aware multiaccess edge computing collaboration model for 5G

In 5G cloud computing, the most notable and considered design issues are the energy efficiency and delay. The majority of the recent studies were dedicated to optimizing the delay issue by leveraging the edge computing concept, while other studies directed its efforts towards realizing a green cloud by minimizing the energy consumption in the cloud. Active queue management‐based green cloud model (AGCM) as one of the recent green cloud models reduced the delay and energy consumption while maintaining a reliable throughput. Multiaccess edge computing (MEC) was established as a model for the edge computing concept and achieved remarkable enhancement to the delay issue. In this paper, we present a handoff scenario between the two cloud models, AGCM and MEC, to acquire the potential gain of such collaboration and investigate its impact on the cloud fundamental constraints; energy consumption, delay, and throughput. We examined our proposed model with simulation showing great enhancement for the delay, energy consumption, and throughput over either model when employed separately.     

Low‐jitter slot assignment algorithm for deadline‐aware packet transmission in wireless video surveillance sensor networks

This work presents a distributed time‐slot assignment algorithm which adopts TDMA as Medium Access Control, specially suited to support applications with strict delay, jitter, and throughput requirements characterized by convergecast traffic pattern in sensor networks. (e.g. wireless video surveillance sensor networks). The proposed algorithm has three characteristics: (1) every node is guaranteed a path to the base station for its data delivery. In the path, sufficient resource is reserved and weighted fairness can be achieved. (2) It uses cascading time‐slot assignment and jitter minimization algorithm in each node to minimize jitter and end‐to‐end delay. (3) Nodes are only active during their scheduled slots and sleep otherwise. This offers energy saving by reducing idle listening and avoiding overhearing. The performance of the proposed algorithm is evaluated over simulations and analyzed theoretically in comparison with existing slot assignment algorithm. The results show that our algorithm provides lower end‐to‐end delay, jitter, and higher throughput. Copyright © 2010 John Wiley & Sons, Ltd.     

Homing‐pigeon‐based messaging: multiple pigeon‐assisted delivery in delay‐tolerant networks

In this paper, we consider the applications of delay‐tolerant networks (DTNs), where the nodes in a network are located in separated areas, and in each separated area, there exists (at least) an anchor node that provides regional network coverage for the nearby nodes. The anchor nodes are responsible for collecting and distributing messages for the nodes in the vicinity. This work proposes to use a set of messengers (named pigeons) that move around the network to deliver messages among multiple anchor nodes. Each source node (anchor node or Internet access point) owns multiple dedicated pigeons, and each pigeon takes a round trip starting from its home (i.e., the source) through the destination anchor nodes and then returns home, disseminating the messages on its way. We named this as a homing‐pigeon‐based messaging (HoPM) scheme. The HoPM scheme is different from the prior schemes in that each messenger is completely dedicated to its home node for providing messaging service. We obtained the average message delay of HoPM scheme in DTN through theoretical analysis with three different pigeon scheduling schemes. The analytical model was validated by simulations. We also studied the effects of several key parameters on the system performance and compared the results with previous solutions. The results allowed us to better understand the impacts of different scheduling schemes on the system performance of HoPM and demonstrated that our proposed scheme outperforms the previous ones. Copyright © 2011 John Wiley & Sons, Ltd.     

Study of capacity region and minimum energy of delay‐tolerant unicast mobile ad hoc networks using cell‐partitioned model

Capacity region and minimum energy function for a variety of delay‐tolerant mobile unicast ad hoc networks are studied by using a cell‐partitioned model. First, theorems about analytical expressions of network capacity and upper bound of minimum energy function are proposed and proved. Algorithm aiming at maximizing capacity and minimizing energy cost is presented and analyzed by Lyapunov drift method. Second, these two theorems are applied to several types of ad hoc networks. Expressions of network capacity and minimum energy function are obtained. Third, capacity property of a type of hybrid ad hoc networks is analyzed in detail. Relationship among limitation of capacity, node density, and coverage of base stations are investigated. Numerical analysis and simulation are carried out. Copyright © 2015 John Wiley & Sons, Ltd.     

Energy‐efficient multihop routing in WSN using the hybrid optimization algorithm

The technical growth in the field of the wireless sensor networks (WSNs) has resulted in the process of collecting and forwarding the massive data between the nodes, which was a major challenge to the WSNs as it is associated with greater energy loss and delay. This resulted in the establishment of a routing protocol for the optimal selection of the multipath to progress the routing in WSNs. This paper proposes an energy‐efficient routing in WSNs using the hybrid optimization algorithm, cat–salp swarm algorithm (C‐SSA), which chooses the optimal hops in progressing the routing. Initially, the cluster heads (CHs) are selected using the low‐energy adaptive clustering hierarchy (LEACH) protocol that minimizes the traffic in the network. The CHs are engaged in the multihop routing, and the selection of the optimal paths is based on the proposed hybrid optimization, which chooses the optimal hops based on the energy constraints, such as energy, delay, intercluster distance, intracluster distance, link lifetime, delay, and distance. The simulation results prove that the proposed routing protocol acquired minimal delay of 0.3165 with 50 nodes and two hops, maximal energy of 0.1521 with 50 nodes and three hops, maximal number of the alive nodes as 39 with 100 nodes and two hops, and average throughput of 0.9379 with 100 nodes and three hops.     

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.     

Time‐aware and energy‐efficient opportunistic routing with residual energy collection in wireless sensor networks

In 1‐dimensional queue wireless sensor networks, how to balance end‐to‐end latency and energy consumption is a challenging problem. However, traditional best path routing and existing opportunistic routing protocols do not address them well because relay hop counts are usually much more, and the link appears more unreliable compared with general mesh topology. In this work, we formulate these 2 problems as a multiobjective optimization problem. Specifically, we first classify network packets into types of time tolerant and time critical and introduce a residual energy collection mechanism of neighboring nodes for forwarder set selection. We then propose a time‐aware and energy‐efficient opportunistic routing protocol (TE‐OR) to optimize energy consumption and to reduce latency for time‐critical packets. We evaluate TE‐OR by different parameters and compare it with existing protocols. The performance results show that TE‐OR achieves a trade‐off between energy consumption and time delay and balances energy consumption among nodes while guaranteeing the latency of time‐critical packets is minimized.