A delay‐bounded routing protocol for vehicular ad hoc networks with traffic lights

In vehicular ad hoc networks, vehicles may use a routing protocol to inform emergent events, for example, car accidents or traffic jams. Hence, many of the researchers are focused on minimizing the end‐to‐end delay of the routing protocol. However, some applications, for example, email or ftp, are not time critical, and radio spectrum is a limited resource. Hence, delay‐bounded routing protocol, whose goal is to deliver messages to the destination within user‐defined delay and minimize the usage of radio, has become an important issue. The delay‐bounded routing protocols deliver message to the destination by the hybrid of data muling (carried by the vehicle) and forwarding (transmitted through radio). When the available time is enough, the message will be delivered by muling; otherwise, it will be delivered by forwarding. However, in an urban area, there are many traffic lights, which may greatly affect the performance of the delay‐bounded routing protocols. Existing works do not consider the effect of traffic lights, and hence, it may adopt an improper delivery strategy and thus wastes much available time. To improve previous works, we propose a novel delay‐bounded routing protocol, which has considered the effect of traffic lights. Whenever a vehicle passes an intersection, it will gather the information of the traffic light and traffic load of the next road section, and thus, it can make a more accurate prediction and adopt a more proper strategy to deliver message. Simulation results show that the proposed protocol can make a better usage of the available time and uses less radio resource to deliver the message in time. Copyright © 2013 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.     

Multi‐interface cognitive radio for enhanced routing in multi‐hop cellular networks

Multi‐hop cellular network (MCN) is a wireless communication architecture that combines the benefits of conventional single‐hop cellular networks and multi‐hop ad hoc relaying networks. The route selection in MCN depends on the availability of intermediate nodes and their neighborhood connectivity. Cognitive radio (CR) is an emerging communication paradigm that exploits the available radio frequencies opportunistically for the effective utilization of the radio frequency spectrum. The incorporation of CR and mobile ad hoc network routing protocols in MCN could potentially improve the spectrum utilization and the routing performance of MCN. This paper firstly presents the proposed model for the multi‐interface CR mobile node with transceiver synchronization and then investigates its opportunistic spectrum utilization and routing performance in MCN. Copyright © 2015 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.     

Packet‐level‐based traffic aggregation to optimize NDN content delivery

In recent years, named data networking (NDN) has been accepted as the most popular future paradigm and attracted much attention, of which the routing model contains interest forwarding and content delivery. However, interest forwarding is far from the bottleneck of routing optimization; instead, the study on content delivery can greatly promote routing performance. Although many proposals on content delivery have been investigated, they have not considered packet‐level caching and deep traffic aggregation, which goes against the performance optimization of content delivery. In this paper, we propose a packet‐level‐based traffic aggregation (PLTA) scheme to optimize NDN content delivery. At first, the packet format is devised, and data plane development kit (DPDK) is used to ensure same size for each packet. Then, the whole delivery scheme with traffic aggregation consideration is presented. The simulation is driven by the real YouTube dataset over Deltacom, NSFNET, and CERNET topologies, and the experimental results demonstrate that the proposed PLTA has better delivery performance than three baselines in terms of cache hit ratio, delivery delay, network load, and energy efficiency.     

Hopfield neural‐network‐based dynamic resource allocation scheme for non‐real‐time traffic in wireless networks

Dynamic resource allocation (DRA) plays a fundamental role in current and future wireless networks, including 3G systems. In this paper, a scheduling DRA scheme for non‐real‐time (NRT) packet services in wireless system is proposed based on the use of Hopfield neural networks (HNN). The scheme exploits the fast response time of HNN for solving NP optimization problems and has been particularized for the downlink transmission in a UMTS system, although it could be easily extended to any other radio access technology. The new DRA scheme follows a delay‐centric approach, since it maximizes the overall system resource utilization while minimizing the packet delay. Simulation results confirm that the proposed HNN‐based DRA scheme is effective in supporting different types of NRT services, while achieving efficient utilization of radio resources. Copyright © 2008 John Wiley & Sons, Ltd.     

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.     

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.     

An energy‐efficient asynchronous wake‐up scheme for underwater acoustic sensor networks

In addition to the requirements of the terrestrial sensor network where performance metrics such as throughput and packet delivery delay are often emphasized, energy efficiency becomes an even more significant and challenging issue in underwater acoustic sensor networks, especially when long‐term deployment is required. In this paper, we tackle the problem of energy conservation in underwater acoustic sensor networks for long‐term marine monitoring applications. We propose an asynchronous wake‐up scheme based on combinatorial designs to minimize the working duty cycle of sensor nodes. We prove that network connectivity can be properly maintained using such a design even with a reduced duty cycle. We study the utilization ratio of the sink node and the scalability of the network using multiple sink nodes. Simulation results show that the proposed asynchronous wake‐up scheme can effectively reduce the energy consumption for idle listening and can outperform other cyclic difference set‐based wake‐up schemes. More significantly, high performance is achieved without sacrificing network connectivity. Copyright © 2015 John Wiley & Sons, Ltd.     

Nash bargaining solution based joint time‐frequency‐code‐power resource management algorithm for TD‐LTE systems

This paper presents a joint time‐frequency‐code‐power resource management algorithm based on the Nash bargaining solution in time‐division long term evolution systems. First, a joint radio resource allocation scheme at the time, frequency, code and power domain simultaneously is provided for the time‐division long term evolution system. Second, the proposed algorithm is modeled as a cooperative game under the constraints of each user's minimal rate requirement and available resources, for example, the maximal transmitting power. To reduce the computational complexity, the joint resource allocation algorithm is divided into time‐frequency‐code and power domain resource allocation. Also, we could approach the Pareto optimal rate as closely as possible by iterations. Simulation results show that compared with the other resource allocation algorithms, the proposed algorithm has achieved a good tradeoff between the overall system throughput and fairness among different users. Copyright © 2012 John Wiley & Sons, Ltd.     

End-to-end bandwidth allocation scheme for voice traffic support over MANETs

Multimedia and real-time applications require bandwidth guarantees, which can be achieved by resource reservation. However, bandwidth reservation in ad-hoc networks is a very challenging task due to the instability of radio channels, node mobility and lack of coordination between mobile nodes. Most proposed reservation protocols focus on point-to-point reservations, and only a few work has been done to propose an efficient end-to-end reservation scheme. In this paper, we propose a reservation scheme called End-to-end reservation scheme for voice and data traffic support (EERV). The basic component of our protocol is a handshake mechanism which has the role to establish point-to-point reservations, and to ensure consistency of reservations between neighbor nodes. Both data and voice sources are allowed to establish reservations with priority given to voice sources. This reservation scheme is extended to support the reservation and release of resources along a path in cooperation with the routing layer. Our reservation scheme is based on DSR, a well-known reactive routing protocol. Mobility of nodes and node failure cause frequent reservation breakages resulting in significant performance degradation. In order to resolve this issue we propose a reservation loss detection and reservation recovery mechanisms. We achieved intensive simulations to evaluate the performance of our protocol. Simulation results show the effectiveness of this protocol.     

Linear regression‐based delay‐bounded routing protocols for VANETs

Routing protocols for vehicular ad hoc networks (VANETs) have attracted a lot of attention recently. Most of the researches emphasize on minimizing the end‐to‐end delay without paying attention to reducing the usage of radio. This paper focuses on delay‐bounded routing, whose goal is to deliver messages to the destination within user‐defined delay and to minimize the usage of radio because radio spectrum is a limited resource. The messages can be delivered to the destination by the hybrid of data muling (carried by the vehicle) and forwarding (transmitted through radio). In the existing protocol, a vehicle may only switch the delivery strategy (muling or forwarding) at an intersection according to the available time of the next road segment, which is between the current intersection and the next intersection. To improve previous works, our protocol uses linear regression to predict the available time and the traveling distance, and thus, the vehicle can switch to a proper delivery strategy at a proper moment and can reduce the number of relays by radio. Our protocol contains two schemes: the greedy and centralized schemes. The greedy scheme uses only the current sampling data to predict the available time and decide when to switch the delivery strategy, whereas the centralized scheme uses the global statistical information to choose a minimum‐cost path. Simulation results justify the efficiency of the proposed protocol. Copyright © 2011 John Wiley & Sons, Ltd.     

An efficient in‐network caching decision algorithm for Internet of things

Recently, content‐centric networking (CCN) has become one of the important technologies for enabling the future networks. Along with its recognized potentialities as a content retrieval and dissemination solution, CCN has been also recently considered as a promising architecture for the Internet of things (IoT), because of 2 main features such as named‐based routing and in‐network caching. However, IoT is characterized by challenging features: small storage capacity of resource‐constrained devices due to cost and limitation of energy and especially transient data that impose stringent requirements on the information freshness. As a consequence, the intrinsic caching mechanisms existing in CCN approach do not well suit IoT domains; hence, providing a specific caching policy at intermediate nodes is a very challenging task. This paper proposes an effective multiattribute in‐network caching decision algorithm that performs a caching strategy in CCN‐IoT network by considering a set of crucial attributes including the content store size, hop count, particularly key temporal properties like data freshness, and the node energy level. Simulation results proved that our proposed approach outperforms 2 cache management schemes (probabilistic least recently used and AlwaysCache–first in first out in terms of improving total hit rate, reducing data retrieval delay, and enhancing content reusability in IoT environment).     

Topology control‐based collaborative multicast routing algorithm with minimum energy consumption

This paper studies the multicast routing problem in the multi‐hop wireless network. We exploit topology control to put forward a multicast routing algorithm with minimum energy consumption. First, network nodes are classified as different clusters. Then, the end‐to‐end multicast routing is appropriately built by using the cooperation among clusters and in each cluster and by minimizing the energy consumption. Unlike previous methods, we employ the appropriate cooperation among/in clusters and the optimal cross‐layer design to attain the information from the different layers and the different nodes. In a result, on the basis of the information, the needed clusters of nodes are correctly created. This is helpful to avoid clustering blindly network nodes and to reduce computational overheads. Simulation results show that the proposed algorithm is promising and effective. Copyright © 2014 John Wiley & Sons, Ltd.     

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.     

认知无线电网络中基于协作中继的资源分配算法

在认知无线电网络的协作中继机制下,中继节点利用其和源节点以及目的节点的不同公共信道为二者的通信转发数据,可以有效解决次用户的通信需求和可用带宽之间的矛盾,提高频谱利用率和系统吞吐量。基于协作中继的认知无线电网络中,不同通信链路上可能存在公共可用信道,使信道和中继的分配问题变得复杂。本文研究了公共信道存在的情况下系统的资源分配问题,基于网络最大流理论提出了两种算法:并行算法和贪婪算法,并分析了算法复杂度。仿真结果表明,两种算法都能够更有效地分配资源,提高频谱利用率,改善网络吞吐量。并行算法可以得到最优解,但其复杂度随信道公用程度的上升增长迅速,受节点并行处理能力的限制,只适用于信道公用程度较低的情况。贪婪算法不一定能得到最优解,但其复杂度较低,并且信道公用程度高时接近最优解,因此超出节点的并行处理能力后,可以选择贪婪算法。      

A green cluster‐based routing scheme for large‐scale wireless sensor networks

In wireless sensor networks (WSNs), clustering has been shown to be an efficient technique to improve scalability and network lifetime. In clustered networks, clustering creates unequal load distribution among cluster heads (CHs) and cluster member (CM) nodes. As a result, the entire network is subject to premature death because of the deficient active nodes within the network. In this paper, we present clustering‐based routing algorithms that can balance out the trade‐off between load distribution and network lifetime “green cluster‐based routing scheme.” This paper proposes a new energy‐aware green cluster‐based routing algorithm to preventing premature death of large‐scale dense WSNs. To deal with the uncertainty present in network information, a fuzzy rule‐based node classification model is proposed for clustering. Its primary benefits are flexibility in selecting effective CHs, reliability in distributing CHs overload among the other nodes, and reducing communication overhead and cluster formation time in highly dense areas. In addition, we propose a routing scheme that balances the load among sensors. The proposed scheme is evaluated through simulations to compare our scheme with the existing algorithms available in the literature. The numerical results show the relevance and improved efficiency of our scheme.     

Joint spectrum sensing and resource allocation optimization using genetic algorithm for frequency hopping–based cognitive radio networks

In cognitive radio (CR) networks, secondary users should effectively use unused licensed spectrums, unless they cause any harmful interference to the primary users. Therefore, spectrum sensing and channel resource allocation are the 2 main functionalities of CR networks, which play important roles in the performance of a CR system. To maximize the CR system utility, we propose a joint out‐of‐band spectrum sensing and operating channel allocation scheme based on genetic algorithm for frequency hopping–based CR networks. In this paper, to effectively sense the primary signal on hopping channels at each hopping slot time, a set of member nodes sense the next hopping channel, which is called out‐of‐band sensing. To achieve collision‐free cooperative sensing reporting, the next channel detection notification mechanism is presented. Using genetic algorithm, the optimum sensing and data transmission schedules are derived. It selects a sensing node set that participate the spectrum sensing for the next expected hopping channel during the current channel hopping time and another set of nodes that take opportunity for transmitting data on the current hopping channel. The optimum channel allocation is performed in accordance with each node's individual traffic demand. Simulation results show that the proposed scheme can achieve reliable spectrum sensing and efficient channel allocation.     

A cluster‐based fault‐tolerant routing protocol for wireless sensor networks

Energy conservation and fault tolerance are two critical issues in the deployment of wireless sensor networks (WSNs). Many cluster‐based fault‐tolerant routing protocols have been proposed for energy conservation and network lifetime maximization in WSNs. However, these protocols suffer from high frequency of re‐clustering as well as extra energy consumption to tolerate failures and consider only some very normal parameters to form clusters without any verification of the energy sufficiency for data routing. Therefore, this paper proposes a cluster‐based fault‐tolerant routing protocol referred as CFTR. This protocol allows higher energy nodes to become Cluster Heads (CHs) and operate multiple rounds to diminish the frequency of re‐clustering. Additionally, for the sake to get better energy efficiency and balancing, we introduce a cost function that considers during cluster formation energy cost from sensor node to CH, energy cost from CH to sink, and another significant parameter, namely, number of cluster members in previous round. Further, the proposed CFTR takes care of nodes, which have no CH in their communication range. Also, it introduces a routing algorithm in which the decision of next hop CH selection is based on a cost function conceived to select routes with sufficient energy for data transfer and distribute uniformly the overall data‐relaying load among the CHs. As well, a low‐overhead algorithm to tolerate the sudden failure of CHs is proposed. We perform extensive simulations on CFTR and compare their results with those of two recent existing protocols to demonstrate its superiority in terms of different metrics.