An Adaptive Routing Algorithm for Integrated Information Networks

The integrated information network is a large capacity information network that integrates various communication platforms on the ground, at sea, in the air and in the deep air through the inter-satellite and satellite-ground links to acquire information accurately, process it quickly, and transmit it efficiently. The satellite communication, as an important part of integrated information networks, is one of main approaches to acquire, process and distribute communication information and resources. In this paper, based on current researches of the satellite communication network, we put forward a 3-layer satellite communication network model based on the Software Defined Network (SDN). Meanwhile, to improve current routing policies of the Low Earth Orbit (LEO) satellite communication network, we put forward an Adaptive Routing Algorithm (ARA) to sustain the shortest satellite communication link. Experiment results show that the proposed method can effectively reduce link distance and communication delay, and realize adaptive path planning.

A Discrete-Time Traffic and Topology Adaptive Routing Algorithm for LEO Satellite Networks

“Minimizing path delay” is one of the challenges in low Earth orbit (LEO) satellite network routing algo-rithms. Many authors focus on propagation delays with the distance vector but ignore the status information and processing delays of inter-satellite links. For this purpose, a new discrete-time traffic and topology adap-tive routing (DT-TTAR) algorithm is proposed in this paper. This routing algorithm incorporates both inher-ent dynamics of network topology and variations of traffic load in inter-satellite links. The next hop decision is made by the adaptive link cost metric, depending on arrival rates, time slots and locations of source-destination pairs. Through comprehensive analysis, we derive computation formulas of the main per-formance indexes. Meanwhile, the performances are evaluated through a set of simulations, and compared with other static and adaptive routing mechanisms as a reference. The results show that the proposed DT-TTAR algorithm has better performance of end-to-end delay than other algorithms, especially in high traffic areas.

Adaptive swarm-based routing in communication networks

Swarm intelligence inspired by the social behavior of ants boasts a number of attractive features, including adaptation, robustness and distributed, decentralized nature, which are well suited for routing in modern communication networks. This paper describes an adaptive swarm-based routing algorithm that increases convergence speed, reduces routing instabilities and oscillations by using a novel variation of reinforcement learning and a technique called momentum.Experiment on the dynamic network showed that adaptive swarm-based routing learns the optimum routing in terms of convergence speed and average packet latency.

AFAR:adaptive fuzzy ant-based routing for communication networks

We propose a novel approach called adaptive fuzzy ant-based routing (AFAR), where a group of intelligent agents (or ants) builds paths between a pair of nodes, exploring the network concurrently and exchanging obtained information to up-date the routing tables. Routing decisions can be made by the fuzzy logic technique based on local information about the current network state and the knowledge constructed by a previous set of behaviors of other agents. The fuzzy logic technique allows multiple constraints such as path delay and path utilization to be considered in a simple and intuitive way. Simulation tests show that AFAR outperforms OSPF, AntNet and ASR, three of the currently most important state-of-the-art algorithms, in terms of end-to-end delay, packet delivery, and packet drop ratio. AFAR is a promising alternative for routing of data in next generation networks.

A DTN Oriented Adaptive Routing Algorithm Based on Node Load

In recent years,Delay Tolerant Networks(DTN)have received more and more attention.At the same time,several existing DTN routing algorithms generally have disadvantages such as poor scalability and inability to perceive changes in the network environment.This paper proposes an AdaptiveSpray routing algorithm.The algorithm can dynamically control the initial maximum message copy number according to the cache occupancy rate of the node itself,and the cache occupancy rate is added as an impact factor to the calculation of the probability of each node meeting the destination node.In the forwarding phase,the node will first compare the meeting probability of itself and the meeting node to the destination node,and then choose different forwarding strategies.The simulation shows that the AdaptiveSpray algorithm proposed in this paper has obvious advantages compared with the existing routing algorithms in terms of message delivery rate and average delay.

Adaptive Multi-Cost Routing Protocol to Enhance Lifetime for Wireless Body Area Network

Wireless Body Area Network(WBAN)technologies are emerging with extensive applications in several domains.Health is a fascinating domain of WBAN for smart monitoring of a patient’s condition.An important factor to consider in WBAN is a node’s lifetime.Improving the lifetime of nodes is critical to address many issues,such as utility and reliability.Existing routing protocols have addressed the energy conservation problem but considered only a few parameters,thus affecting their performance.Moreover,most of the existing schemes did not consider traffic prioritization which is critical in WBANs.In this paper,an adaptive multi-cost routing protocol is proposed with a multi-objective cost function considering minimum distance from sink,temperature of sensor nodes,priority of sensed data,and maximum residual energy on sensor nodes.The performance of the proposed protocol is compared with the existing schemes for the parameters:network lifetime,stability period,throughput,energy consumption,and path loss.It is evident from the obtained results that the proposed protocol improves network lifetime and stability period by 30%and 15%,respectively,as well as outperforms the existing protocols in terms of throughput,energy consumption,and path loss.

Adaptive Routing Algorithms and Implementation for TESH Network

The Tori-connected mESH (TESH) Network is a k-ary n-cube networks of multiple basic modules, in which the basic modules are 2D-mesh networks that are hierarchically interconnected for higher level k-ary n-cube networks. Many adaptive routing algorithms for k-ary n-cube networks have already been proposed. Thus, those algorithms can also be applied to TESH network. We have proposed three adaptive routing algorithms—channel-selection, link-selection, and dynamic dimension reversal—for the efficient use of network resources of a TESH network to improve dynamic communication performance. In this paper, we implement these routers using VHDL and evaluate the hardware cost and delay for the proposed routing algorithms and compare it with the dimension order routing. The delay and hardware cost of the proposed adaptive routing algorithms are almost equal to that and slightly higher than that of dimension order routing, respectively. Also we evaluate the communication performance with hardware implementation. It is found that the communication performance of a TESH network using these adaptive algorithms is better than when the dimension-order routing algorithm is used.

Improvisation of Node Mobility Using Cluster Routing-based Group Adaptive in MANET

In today's Internet routing infrastructure,designers have addressed scal-ing concerns in routing constrained multiobjective optimization problems examining latency and mobility concerns as a secondary constrain.In tactical Mobile Ad-hoc Network(MANET),hubs can function based on the work plan in various social affairs and the internally connected hubs are almost having the related moving standards where the topology between one and the other are tightly coupled in steady support by considering the touchstone of hubs such as a self-sorted out,self-mending and self-administration.Clustering in the routing process is one of the key aspects to increase MANET performance by coordinat-ing the pathways using multiple criteria and analytics.We present a Group Adaptive Hybrid Routing Algorithm(GAHRA)for gathering portability,which pursues table-driven directing methodology in stable accumulations and on-request steering strategy for versatile situations.Based on this aspect,the research demonstrates an adjustable framework for commuting between the table-driven approach and the on-request approach,with the objectives of enhancing the out-put of MANET routing computation in each hub.Simulation analysis and replication results reveal that the proposed method is promising than a single well-known existing routing approach and is well-suited for sensitive MANET applications.

Optimization of Air Route Network Nodes to Avoid ″Three Areas″ Based on An Adaptive Ant Colony Algorithm

Air route network(ARN)planning is an efficient way to alleviate civil aviation flight delays caused by increasing development and pressure for safe operation.Here,the ARN shortest path was taken as the objective function,and an air route network node(ARNN)optimization model was developed to circumvent the restrictions imposed by″three areas″,also known as prohibited areas,restricted areas,and dangerous areas(PRDs),by creating agrid environment.And finally the objective function was solved by means of an adaptive ant colony algorithm(AACA).The A593,A470,B221,and G204 air routes in the busy ZSHA flight information region,where the airspace includes areas with different levels of PRDs,were taken as an example.Based on current flight patterns,a layout optimization of the ARNN was computed using this model and algorithm and successfully avoided PRDs.The optimized result reduced the total length of routes by 2.14% and the total cost by 9.875%.

Adaptive Route Sink Relocation Using Cluster Head Chain Cycling Model in WSN

Wireless Sensor Networks(WSN)have revolutionized the processes involved in industrial communication.However,the most important challenge faced by WSN sensors is the presence of limited energy.Multiple research inves-tigations have been conducted so far on how to prolong the energy in WSN.This phenomenon is a result of inability of the network to have battery powered-sensor terminal.Energy-efficient routing on packetflow is a parallel phenomenon to delay nature,whereas the primary energy gets wasted as a result of WSN holes.Energy holes are present in the vicinity of sink and it is an important efficient-routing protocol for WSNs.In order to solve the issues discussed above,an energy-efficient routing protocol is proposed in this study named as Adaptive Route Decision Sink Relocation Protocol using Cluster Head Chain Cycling approach(ARDSR-CHC2H).The proposed method aims at improved communica-tion at sink-inviting routes.At this point,Cluster Head Node(CHN)is selected,since it consumes low energy and permits one node to communicate with others in two groups.The main purpose of the proposed model is to reduce energy con-sumption and define new interchange technology.A comparison of simulation results demonstrates that the proposed algorithm achieved low cluster creation time,better network error and high Packet Delivery Rate with less network failure.

Connectivity-Enhanced Route Selection and Adaptive Control for the Chevrolet Volt

The National Renewable Energy Laboratory and General Motors evaluated connectivity-enabled efficiency enhancements for the Chevrolet Volt. A high-level model was developed to predict vehicle fuel and electricity consumption based on driving characteristics and vehicle state inputs. These techniques were leveraged to optimize energy efficiency via green routing and intelligent control mode scheduling, which were evaluated using prospective driving routes between tens of thousands of real-world origin/destination pairs. The overall energy savings potential of green routing and intelligent mode scheduling was estimated at 5% and 3%, respectively. These represent substantial opportunities considering that they only require software adjustments to implement.

PERFORMANCE ANALYSIS OF MINIMAL PATH FAULT TOLERANT ROUTING IN NOC

Occurrence of faults in Network on Chip(NoC) is inevitable as the feature size is con-tinuously decreasing and processing elements are increasing in numbers.Faults can be revocable if it is transient.Transient fault may occur inside router,or in the core or in communication wires.Examples of transient faults are overflow of buffers in router,clock skew,cross talk,etc..Revocation of transient faults can be done by retransmission of faulty packets using oblivious or adaptive routing algorithms.Irrevocable faults causes non-functionality of segment and mainly occurs during fabrication process.NoC reliability increases with the efficient routing algorithms,which can handle the maximum faults without deadlock in network.As transient faults are temporary and can be easily revoked using re-transmission of packet,permanent faults require efficient routing to route the packet by bypassing the nonfunctional segments.Thus,our focus is on the analysis of adaptive minimal path fault tolerant routing to handle the permanent faults.Comparative analysis between partial adaptive fault tolerance routing West-First,North-Last,Negative-First,Odd Even,and Minimal path Fault Tolerant routing(MinFT) algorithms with the nodes and links failure is performed using NoC Interconnect RoutinG and Application Modeling simulator(NIRGAM) for the 2D Mesh topology.Result suggests that MinFT ensures data transmission under worst conditions as compared to other adaptive routing algorithms.

Novel Energy-Efficient Opportunistic Routing Protocol for Marine Wireless Sensor Networks Based on Compressed Sensing and Power Control

In marine wireless sensor networks(MWSNs),an appropriate routing protocol is the key to the collaborative collection and efficient transmission of massive data.However,designing an appropriate routing protocol under the condition of sparse marine node deployment,highly dynamic network topology,and limited node energy is complicated.Moreover,the absence of continuous endto-end connection introduces further difficulties in the design of routing protocols.In this case,we present a novel energy-efficient opportunistic routing(Novel Energy-Efficient Opportunistic Routing,NEOR)protocol for MWSNs that is based on compressed sensing and power control.First,a lightweight time-series prediction method-weighted moving average method is proposed to predict the packet advancement value such that the number of location information that is exchanged among a node and its neighbor nodes can be minimized.Second,an adaptive power control mechanism is presented to determine the optimal transmitting power and candidate nodeset on the basis of node mobility,packet advancement,communication link quality,and remaining node energy.Subsequently,a timer-based scheduling algorithm is utilized to coordinate packet forwarding to avoid packet conflict.Furthermore,we introduce the compressed sensing theory to compress perceptual data at source nodes and reconstruct the original data at sink nodes.Therefore,energy consumption in the MWSNs is greatly reduced due to the decrease in the amount of data perception and transmission.Numerical simulation experiments are carried out in a wide range of marine scenarios to verify the superiority of our approach over selected benchmark algorithms.

Cluster Based Hierarchical Routing Algorithm for Network on Chip

This paper presents a new logical mechanism called as Cluster Based Hierarchical Routing (CBHR) to improve the efficiency of NoC. This algorithm comprises the following steps: 1) the network is segmented logically into clusters with same size or different sizes;2) algorithms are assigned for internal and global routing;3) routers working functions are modified logically to support local and global communication. The experiments have conducted for CBHR algorithm for two dimensional mesh and torus architectures. The performance of this mechanism is analyzed and compared with other deterministic and adaptive routing algorithms in terms of energy, throughput with different packet injection ratios.

DECLARATIVE HYBRID ROUTING PROTOCOLS IN AD HOC NETWORKS

This paper presents adaptive hybrid protocols based on the declarative network and mainly discusses the principle and realization of the Bayesian-estimation based adaptive hybrid protocol in the declarative network, which is well adapted to the Mobile Ad hoc NETwork (MANET). The adaptive hybrid protocol is designed for ad hoc networks which have characteristics like self-organizing, no trusted party, flexibility, etc. The nodes that run the hybrid protocol can automatically select one routing protocol that is suitable for different network environment. The Bayesian-estimation based adaptive strategy, that improves the adaptability and stability of the protocol, succeeds in the Rapidnet, a declarative network engine. The result in the Rapidnet proves that the hybrid protocol and the adaptive strategy are feasible. The experiment on the ns-3 simulator, an emerging discrete-event network simulator, validates that this protocol performs well and reduces communication overheads.

Cluster Head Selection and Multipath Routing Based Energy Efficient Wireless Sensor Network

The Wireless Sensor Network(WSN)is a network of Sensor Nodes(SN)which adopt radio signals for communication amongst themselves.There is an increase in the prominence of WSN adaptability to emerging applications like the Internet of Things(IoT)and Cyber-Physical Systems(CPS).Data secur-ity,detection of faults,management of energy,collection and distribution of data,network protocol,network coverage,mobility of nodes,and network heterogene-ity are some of the issues confronted by WSNs.There is not much published information on issues related to node mobility and management of energy at the time of aggregation of data.Towards the goal of boosting the mobility-based WSNs’network performance and energy,data aggregation protocols such as the presently-used Mobility Low-Energy Adaptive Clustering Hierarchy(LEACH-M)and Energy Efficient Heterogeneous Clustered(EEHC)scheme have been exam-ined in this work.A novel Artificial Bee Colony(ABC)algorithm is proposed in this work for effective election of CHs and multipath routing in WSNs so as to enable effective data transfer to the Base Station(BS)with least energy utilization.There is avoidance of the local optima problem at the time of solution space search in this proposed technique.Experimentations have been conducted on a large WSN network that has issues with mobility of nodes.

需求不确定下的两阶段应急物流选址-路径研究

针对灾后应急救援在需求不确定和资源受限方面的问题,以多级应急物流网络为背景,构建了一个需求不确定下的两阶段应急选址-路径规划模型。该模型以总成本最小和救援车辆运输总距离最短为目标,采用三角模糊数刻画受灾点的不确定需求,并采用基于可信性的模糊机会约束规划方法,以消除约束条件中的不确定参数。模型第一阶段调用Gurobi求解器,求解得到应急配送中心选址结果和对受灾点的分配方案;第二阶段将选址及分配结果作为输入进行路径规划,并提出一种改进的自适应遗传算法(IAGA)对算例进行求解。然后采用自适应遗传算法(AGA)与之对比,并进行灵敏度分析。结果表明:IAGA在目标值、收敛速度和运行时间等方面均优于AGA,证明了IAGA具有一定的可行性和有效性,且可以为决策者提供较优的应急选址-路径规划方案,从而提升灾后救援的效率。

考虑客户需求重要度的快递包裹配送车辆路径问题

目的针对客户在配送服务方面的个性化和高质量要求,在快递包裹配送过程中考虑客户需求重要度的差异以提高客户服务质量,并降低物流网络的运营总成本。方法首先,考虑客户需求重要度对违反服务时间窗惩罚成本的影响,构建物流运营总成本最小化的数学模型;其次,设计基于Clarke-Wright节约算法的粒子群优化(CW-PSO)算法求解模型,并在算法中引入自适应更新机制,以提高算法的全局搜索能力和求解质量;然后,将CW-PSO算法与遗传-蚁群优化算法、蚁群优化算法和头脑风暴优化算法进行对比分析,验证CW-PSO算法的有效性;最后,以重庆市某快递包裹配送网络为例,比较分析优化前后各项运营指标变化,并进行基于客户需求重要度的敏感度分析。结果优化后车辆使用数减少了38.9%,物流运营总成本降低了43.1%,将客户划分为5类需求重要度等级得到的优化结果具有优越性。结论本研究所提出的优化模型、求解算法和考虑客户需求重要度可有效提高快递包裹配送网络的服务效率并降低物流运营总成本,进而为物流企业的快递包裹配送问题提供理论参考和决策支持。

DAWN: A Density Adaptive Routing for Deadline-Based Data Collection in Vehicular Delay Tolerant Networks

Vehicular Delay Tolerant Networks （DTN） use moving vehicles to sample and relay sensory data for urban areas, making it a promising low-cost solution for the urban sensing and infotainment applications. However, routing in the DTN in real vehicle fleet is a great challenge due to uneven and fluctuant node density caused by vehicle mobility patterns. Moreover, the high vehicle density in urban areas makes the wireless channel capacity an impactful factor to network performance. In this paper, we propose a local capacity constrained density adaptive routing algorithm for large scale vehicular DTN in urban areas which targets to increase the packet delivery ratio within deadline, namely Density Adaptive routing With Node deadline awareness （DAWN）. DAWN enables the mobile nodes awareness of their neighbor density, to which the nodes＇ transmission manners are adapted so as to better utilize the limited capacity and increase the data delivery probability within delay constraint based only on local information. Through simulations on Manhattan Grid Mobility Model and the real GPS traces of 4960 taxi cabs for 30 days in the Beijing city, DAWN is demonstrated to outperform other classical DTN routing schemes in performance of delivery ratio and coverage within delay constraint. These simulations suggest that DAWN is practically useful for the vehicular DTN in urban areas.

A multi-crossover and adaptive island based population algorithm for solving routing problems

We propose a multi-crossover and adaptive island based population algorithm(MAIPA).This technique divides the entire population into subpopulations,or demes,each with a different crossover function,which can be switched according to the efficiency.In addition,MAIPA reverses the philosophy of conventional genetic algorithms.It gives priority to the autonomous improvement of the individuals(at the mutation phase),and introduces dynamism in the crossover probability.Each subpopulation begins with a very low value of crossover probability,and then varies with the change of the current generation number and the search performance on recent generations.This mechanism helps prevent premature convergence.In this research,the effectiveness of this technique is tested using three well-known routing problems,i.e.,the traveling salesman problem(TSP),capacitated vehicle routing problem(CVRP),and vehicle routing problem with backhauls(VRPB).MAIPA proves to be better than a traditional island based genetic algorithm for all these three problems.