Distributed Routing Algorithm Research Articles

Social characteristics-based routing algorithm for a mobile social network

Utilization of social characteristics presents a modern approach in the design of routing protocols for Mobile Social Networks. In this paper, we present a novel routing algorithm called the Social Characteristics-based Distributed Routing Algorithm (SCDRA) for a Mobile Social Network. SCDRA explores community and friendship as social features to effectively route messages. In SCDRA, nodes develop their community in a distributed way based on the concept of a familiar set. Merging of communities of nodes is governed by certain rules. Friendship in SCDRA evolves based on various factors like inter-contact duration, frequency of encounters and successful delivery of messages forwarded in a few past time intervals between the nodes. Routing of messages is accomplished by utilizing community and friendship as social characteristics. Extensive simulation studies performed show that the proposed algorithm performs better when compared to existing algorithms such as Bubble rap, SMART and EpSoc for performance metrics like delivery ratio, overhead ratio and average delivery latency in various scenarios.

Design of High Speed Reconfigurable Distributed Life Time Efficient Routing Algorithm in Wireless Sensor Network

Designing an energy-efficient routing makes the Wireless Sensor Networks (WSN) more effective and attractive for different applications. The WSN communication system power consumption mainly depends on three aspects such as routing cost computation, signal interference, and routing distance. All three factors are equally important in order to improve the network performance. The system reliability and deployment cost depends on the energy efficiency of the WSN. The energy related cost assignment and shortest paths identification are used in existing routing techniques. In the existing routing techniques maximum achievable lifetime and optimal link cost are low. Hence greatest possible performance can be achieved in distributed routing algorithm by finding shortest path. Maximum lifetime and best cost link can be generally obtained using distributed shortest path routing algorithm. In this paper high speed reconfigurable distributed Lifetime-Efficient Routing algorithm is designed to provide route selection outline with low complexity and obtain better performance compared to existing routing algorithm.

Optimal Distribution Method of Photoelectric Sensing Radio Frequency Identification Multi-Tags Using Ant Colony Algorithm

In this study, RFID technology and wireless photoelectric sensor (WOSN) technology were combined in the acquisition of traffic information. RFID tag and photoelectric sensor were used as a node to build a traffic information collection network. To improve the life cycle and load performance of the network, and achieve the optimal distribution among nodes, the ant colony optimization (ACO) algorithm was taken as the research object, and the network node distribution routing algorithm of multiple RFID tags-photoelectric sensor nodes was designed. The improved ACO based on energy and distance was selected for self-organizing distribution, so that the nodes distributed locally could be regarded as a whole. Then, each local head node transmitted information based on the route generated by the improved ACO, so that the traffic information obtained by each head node was sent to the aggregation node at the lowest cost. In the experiment, the multi RFID tag-photoelectric sensor node distribution based on the improved ACO can extend the network life cycle, and achieve a balanced network load.

Achieving Near-Optimal Traffic Engineering Using a Distributed Algorithm in Hybrid SDN

To empower advanced traffic engineering (TE) mechanism, while considering the infeasibility of one-step migration to software-defined networking (SDN), SDN nodes are incrementally deployed into legacy network, which gives rise to hybrid SDN. In hybrid SDN, redirecting flow of every source-destination pair through at least one SDN node, can enhance TE performance and obtain flow manageability, while on the other hand leading to increasing demands of TCAM resources in SDN nodes. In this paper, we make minimization of maximum link utilization as the TE objective, and comply with SDN waypoint enforcement and TCAM resource limitation. We first formulate the TE problem as an integer linear programming (ILP) model and solve it in a centralized manner, where SDN waypoint selection and splitting fractions for each flow are jointly determined. Then, based on a fact that the logically centralized control plane in hybrid SDN is composed of multiple physically decentralized controllers, each of which manages part of SDN nodes, as well as considering a real situation that a centralized solution is infeasible or too fragile for large-scale network, we develop a distributed algorithm deriving from Lagrangian decomposition theory to effectively solve the TE problem. The simulation results indicate that, when 30% of the SDN nodes are deployed, the proposed traffic engineering-aware distributed routing (TEDR) algorithm obtains maximum link utilization comparable to that of full SDN, and has a limited influence on the routing efficiency.

A New Traffic Distribution Routing Algorithm for Low Level VPNs

Virtual Private Networks (VPN) constitute a particular class of shared networks. In such networks, the resources are shared among several customers. The management of these resources requires a high level of automation to obtain the dynamics necessary for the well-functioning of a VPN. In this paper, we consider the problem of a network operator who owns the physical infrastructure and who wishes to deliver VPN service to his customers. These customers may be Internet Service providers, large corporations and enterprises. We propose a new routing approach referred to as Traffic Split Routing (TSR) which splits the traffic as fairly as possible between the network links. We show that TSR outperforms Shortest Path Routing (SPR) in terms of the number of admitted VPN and in terms of Quality of Service.

Research on Cold Chain Logistics Distribution Routing Algorithm Model Based on Customer Satisfaction

In view of the characteristics of cold chain logistics different from ordinary products and the competition within the industry, the distribution of chilled and frozen foods requires the use of refrigerated vehicles, and the cost of transportation and distribution is high. In the study of cold chain logistics, in order to more fully reflect customer satisfaction, this paper establishes a multi-objective optimization model with the lowest distribution cost and the shortest time; then introduces the customer satisfaction index and establishes a multi-objective optimization model of customer satisfaction. Linear processing transforms multiple goals into single-objective optimization problems.

Two-level distributed clustering routing algorithm based on unequal clusters for large-scale Internet of Things networks

According to the recent advancements in communication technologies and the widespread use of smart devices, our environment can be transforming into the Internet of Things (IoT) because it can connect the physical, cyber, and biological world via smart sensors for different purposes. Wireless sensor networks are considered as one of the main infrastructures in the IoT systems. Therefore, decreasing the total energy consumption of sensor nodes and prolonging the network longevity are two important challenges that should be considered. To increase energy efficiency and to improve the network longevity, a two-level distributed clustering routing algorithm based on unequal clusters has been proposed for large-scale IoT systems. The main idea is to decrease the data transmission distances between member nodes and cluster heads to mitigate the hot spot problem by distributing two cluster heads in each cluster, which in turn leads to energy conservation and load balancing. The clustering method is two level due to the benefits it offers for the sensor nodes. First, each node can transfer its data to the nearest cluster head because a primary cluster head and a secondary cluster head have been considered for each cluster. Therefore, the nodes far from the primary cluster head can be organized based on their distances to the closest cluster head to reduce their data transmission distances to the cluster heads. Second, two cluster heads can be replaced with each other in different circumstances. This reduces the overhead of the cluster head selection algorithm in the proposed scheme. Third, the sensor nodes can benefit from the primary and secondary cluster heads to transfer the data to the sink through different paths with the minimum energy consumption. Simulation results indicate that the proposed algorithm has better performance in terms of total energy consumption, total network energy, and network longevity compared to previous similar schemes.

An energy-aware and load balanced distributed geographic routing algorithm for wireless sensor networks with dynamic hole

The increasing usage of wireless sensor networks in human life is an indication of the high importance of this technology. Holes in wireless sensor networks are non-operating areas that can happen for a variety of reasons, like natural obstacles and disasters. Detection and packet routing in the presence of holes have always been the main challenges of facing this technology. As a result, most of the research on wireless sensor networks has been concerned with the problem of routing through bypassing routing holes. Considering the fact that the hole detection method for transmitting data in wireless sensor networks has a considerable impact on the energy consumption of the network, this paper attempts to provide a solution in the field of routing with the aim of increasing the network lifetime. In this method, considering networks with a dynamic hole, a distributed algorithm is proposed that can quickly determine and update the hole boundary. According to the hole, the packets are guided along an escape path around the hole which can improve and extend network lifetime. Results of experimental simulation are compared with the well-known and successful routing methods in the wireless sensor networks. This comparison shows that the proposed method reduces the dead nodes by at least 11% and 8% considering the effect of the time and the number of the nodes, in turn. Furthermore, the network lifetime has been improved by 2.71% based on the effect of the time and 1.47% based on the number of the nodes.

Design & analysis of a distributed routing algorithm towards Internet-wide geocast

Geocast is the concept of sending data packets to nodes in a specified geographical area instead of nodes with a specific address. This forwarding method is valuable in situations where any number of nodes inside a geographic area need to be reached, such as vehicular networking scenarios. To facilitate large scale geocast, a wired network geographic routing algorithm is needed that can route packets efficiently towards a destination area. Our goal is to design an algorithm that can deliver shortest path tree like geographic forwarding while relying purely on distributed data without central knowledge. In this paper we present and implement two algorithms for geographic routing. One algorithm is based purely on distance-vector data. Another, more complicated algorithm is based on path data. We show that our purely distance-vector-based algorithm can come close to the number of links used by a shortest path tree when a small number of routers are present in the destination area. We also show that our path-based algorithm can come close to the link usage of a shortest path tree in almost all geocast situations. We also show that the algorithms converge relatively quickly following link drops.

Distributed routing algorithm with dynamic connection partition for mobile ad hoc networks

Mobile ad hoc networks (MANETs) are attractive for many applications because of their easy-to-use and self-organising nature. However, the routing overhead problem has always been a bottleneck restricting the development of MANETs technology. The reason behind is the traditional blind flooding methods and frequent route initiations caused by node mobility. Reducing routing overhead has a huge impact on saving energy consumption of mobile nodes and improving the MANETs performance. In this study, a distributed dynamic routing algorithm is proposed to establish an efficient routing mechanism for MANETs. Based on the mobility of nodes, a fuzzy positional relationship between nodes is constructed. Using this relationship, an improved routing method is designed. The authors characterise this relationship between nodes and implement the proposed algorithm in an ad hoc routing architecture. The simulation results show that the proposed routing algorithm achieves good performance in reducing routing overhead and improves the efficiency of packet transmissions in MANETs.

Quantifying the impacts of dynamic control in connected and automated vehicles on greenhouse gas emissions and urban NO2 concentrations

Communication between vehicles and road infrastructure can enable more efficient use of the road network and hence reduce congestion in urban areas. This improvement can be enhanced by distributed control due to its lighter computational load and higher reliability. Despite favourable impacts on traffic, little is known about the effects of such systems on near-road air quality. In this study, an End-To-End (E2E) dynamic distributed routing algorithm in Connected and Automated Vehicles (CAVs) was applied in downtown Toronto, to identify whether benefits to network throughput were associated with lower near-road NO2 concentrations. We observe significant reductions in the emissions of Greenhouse Gases (GHGs) with increased penetration of CAVs. Nonetheless, at times, the emissions of nitrogen oxides (NOx) increased with higher CAVs. Besides, a higher frequency and severity of NO2 hot-spots were observed under a 100% CAV scenario. Impacts of the proposed system on electric energy consumption in a full electric vehicle network were also investigated, indicating that the addition of CAVs that are electric did not contribute to high energy savings. We propose that such new transformative technologies in transportation should be designed with air pollution and public health goals.

Proposed Modified Clarke-Wright Saving Algorithm for Capacitated Vehicle Routing Problem

A multi-objective distribution routing algorithm by using modified Clarke and Wright Saving algorithm is presented. The problem to solve is to deliver loads to a number of outlets based load requirement. The objective function to minimize is the distance saving and traveling time of the resulted route started from depot to the outlets and return to the original depot. Problem to solve is generating a distribution route in a week considering traffic condition for each day. The original Clarke and Wright saving algorithm is modified such that the resulted routes (from a depot to some outlets) accommodates some constraints such as the maximum allowable traveling time, maximum number of delivery shifts, and maximum number of vehicles. The algorithm is applied to a distributor company with nine outlets, two vehicles, and two delivery shifts. In addition, the traffic condition on the outlet-to-outlet and the depot-to-outlet routes is considered. The simulation of the proposed algorithm shows that the algorithm can generate routes that comply with shift’s maximum delivery time and the vehicles’ capacities.

A distributed congestion avoidance routing algorithm in mega-constellation network with multi-gateway

Recently several large-scale constellation networks have been proposed, requiring inter-satellite links and multiple gateways to be equipped. The gateway assignment and traffic congestion avoidance issues are of fundamental importance for the network. In this work, we establish the network model for mega-constellation network with multi-gateway by introducing the concept of satellite router and satellite gateway. We propose a distributed routing algorithm consisting of three processes: 1) Gateway assignment; 2) Path candidate region partitioning and 3) Optimal path generation. In Optimal path generation, Longer Side Priority (LSP) strategy is proposed, aiming at maximizing the path searching space. By solving the path survival problem, LSP strategy is proved to perform better in congestion avoidance. Through simulation, we verify the routing algorithm and find the significant effects of seam movement in network performance. Results suggest that the proposed strategy performs better in load balance and congestion avoidance compared with the minimum delay strategy.

New distributed routing algorithm in wireless network models

The wireless sensor network present all sensor hubs to produce an equal proportion of information packages in a WSN. The centers around a sink need to exchange a more noteworthy number of groups and will all in all fail miserably sooner than various focus focuses in light of the way that in vitality usage of sensor focus focuses in system lifetime can be drawn out by altering the correspondence stack around a sink. This paper introduces another way to deal with tackle this issue by thinking about the psychological capacity of hubs. Most importantly, we misuse the directional gathering receiving wires to propose a directional gathering two-advance recreation routing plan to set up multicast tree for remote multi-jump networks. we think about that terminals make utilization of cutting edge energy collection transmission/gathering methods, for example, maximal proportion consolidating gathering of redundancy codes, or on the other hand information accumulation with rate less codes. Aggregate methods increment communication dependability; diminish energy utilization, and abatement inactivity. Our first calculation is incorporated, expecting that routing calculations should be possible at a focal processor with full access to channel state information for the whole framework. We likewise plan two disseminated routing calculations that require just nearby channel state information. essentially, given us to characterize two recursive calculations of the way a chance to weight utilizing the moderate way weights to each transfer, either from the source (forward) or from the Destination (in reverse). In particular, in the task exhibits a Weight Based Synchronization (WBS) conventional that utilizes the extent of synchronized hub groups as an impetus for synchronization. We outline these outcomes by concentrate the base energy routing issue in static aggregate multi-bounce networks for various sending techniques at transfers. Proposed framework empowers noteworthy performance through the most limited way routing.

Intelligent distributed routing scheme based on social similarity for mobile social networks

In mobile social networks (MSNs), the social attributes of nodes are important factors driving the mobility of nodes. By studying the mobility of the daily activities of node carriers, an intelligent distributed routing algorithm based on social context information prediction was proposed. First, we study the data forwarding problem of mobile social networks from two aspects, the daily behavior of mobile nodes and the similarity of social attributes respectively. Then, our algorithm uses BP neural network to predict the encounter regularity of mobile nodes in terms of time and space dimensions. This information can provide a basis for routing decisions. Finally, a routing algorithm with predictive capability is designed in combination with synchronous delivery and asynchronous delivery. Simulation analysis and experimental results show that the proposed routing algorithm can effectively improve the message delivery ratio and reduce the network overhead.

A Prediction Algorithm based on Markov Chains for finding the Minimum Cost Path in a Mobile WSNs

In this paper we propose the usage of a prediction technique based on Markov Chains to predict nodes positions with the aim of obtain short paths at minimum energy consumption. Specifically, the valuable information from the mobility prediction method is provided to our distributed routing algorithm in order to take the best network decisions considering future states of network resources. In this sense, in each network node, the mobility method employed is based on a Markov model to forecast future RSSI states of neighboring nodes for determining if they will be farther or closer within the next steps. The approach is evaluated considering different algorithms such as: Distance algorithm, Distance Away algorithm and Random algorithm. In addition, with the aim of performing comparisons against optimal values, we present a mathematical optimization model for finding the minimum cost path between a source and a destination node considering all network nodes are mobile. This paper is an extended variant of [8].

The idemetric property: when most distances are (almost) the same.

We introduce the idemetric property, which formalizes the idea that most nodes in a graph have similar distances between them, and which turns out to be quite standard amongst small-world network models. Modulo reasonable sparsity assumptions, we are then able to show that a strong form of idemetricity is actually equivalent to a very weak expander condition (PUMP). This provides a direct way of providing short proofs that small-world network models such as the Watts-Strogatz model are strongly idemetric (for a wide range of parameters), and also provides further evidence that being idemetric is a common property. We then consider how satisfaction of the idemetric property is relevant to algorithm design. For idemetric graphs, we observe, for example, that a single breadth-first search provides a solution to the all-pairs shortest paths problem, so long as one is prepared to accept paths which are of stretch close to 2 with high probability. Since we are able to show that Kleinberg's model is idemetric, these results contrast nicely with the well known negative results of Kleinberg concerning efficient decentralized algorithms for finding short paths: for precisely the same model as Kleinberg's negative results hold, we are able to show that very efficient (and decentralized) algorithms exist if one allows for reasonable preprocessing. For deterministic distributed routing algorithms we are also able to obtain results proving that less routing information is required for idemetric graphs than in the worst case in order to achieve stretch less than 3 with high probability: while Ω(n 2) routing information is required in the worst case for stretch strictly less than 3 on almost all pairs, for idemetric graphs the total routing information required is O(nlog(n)).

Threshold-Based Energy-Estimated Distributed Routing Algorithm in Wireless Sensor Network

Threshold-Based Energy-Estimated Distributed Routing Algorithm in Wireless Sensor Network

Packet Loss Differentiation Over Manet Based on a BP Neural Network

An adaptive distributed routing algorithm is essential in MANETs, since there is no central routing system. Actually, there is no central point of coordination; each node is responsible for forwarding data packets to other nodes, thereby acting as router and host. A packet might travel through multiple intermediary ad hoc nodes in order to arrive to its destination, while the nature of wireless multi-hop channel is bringing in various types of packet losses. This paper focuses on three main reasons of online packet losses in MANETs: (1) losses due to wireless link errors; (2) losses due to congestion; and (3) losses due to route alteration. It proposes a deep learning-based algorithm for packet loss discrimination. The algorithm uses the backpropagation neural network (BPNN) concept. We performed simulation experiments for evaluating the performance of the proposed loss discrimination algorithm under different network configurations. Through simulation results, we confirmed that the proposed algorithm improves packet loss discrimination and route alteration in the network. It also reduces congestion and increases network throughput.

Lattice-Based Turn Model for Adaptive Routing

This paper presents a model for designing partially adaptive logic-based distributed routing algorithms. Unlike the previous methods, the Lattice-based Turn Model associates turn prohibitions with the points of different full-rank integer lattices. Due to the generality of the proposed model, existing approaches can be considered a subset of the solution space identified by this work. Morover, we propose three theorems that are instrumental to the design of lattice-based routing algorithms. In particular, the second theorem gives a necessary and sufficient condition to prove that a lattice-based routing algorithm is deadlock-free as long as the lattice basis meets certain requirements. Based on the proposed model, a novel routing algorithm, called lattice-based routing algorithm (LBRA), is presented. Simulation results exhibit encouraging performance improvements over state-of-the-art approaches when considering real and synthetic benchmarks. For instance, average 71 and 18 percent latency reductions are observed under transpose1 traffic compared to, respectively, Odd-Even and Repetitive Turn Model routing algorithms. Furthermore, LBRA achieves up to 38 and 17 percent performance improvement under real traffic as compared to Odd-Even and Repetitive Turn Model routing algorithms.