Routing In Dynamic Networks Research Articles

A Ship Network Dynamic Routing Algorithm Based on Vector Network

Abstract In view of the characteristics of low speed mobile ship network, strong network dynamics and large signal interference, this paper proposes a low-rate mobile sensor network routing algorithm. In mobile wireless sensor networks, network topology changes frequently is a new challenge for resource constrained sensor node. Constantly updated network topology, sensor nodes need to exchange data frequently in order to maintain fresh route, resulting in sensor nodes consume a lot of energy. To solve this problem, to reduce control overhead is considered to be an effctive strategy. In this paper, we present a vector network-based dynamic routes (VNDR) scheme aims to minimize the control cost of the sensor nodes. We propose data exchange based on binary-coded vector address to reduce the control cost, moreover, we present a set of communication rules that govern the routes search procedure thereby requiring little cost of packet analysis to determine the next hop of node. VNDR performance was compared with well known scheme such as SPIN and DD. Simulation results show that, our VNDR scheme reduced the network control overhead and improved network lifetime.

Cost-efficient dynamic quota-controlled routing in multi-community delay-tolerant networks

Delay-tolerant networks are novel wireless mobile networks, which are characterized with high latency and frequent disconnectivity. Besides, people carrying mobile devices form a lot of communities because of similar interests and social relationships. How to improve the routing efficiency in multi-community scenarios has become one of the research hot spots in delay-tolerant networks. In this article, we present a network model of the multi-community delay-tolerant networks and formulate a dynamic quota-controlled routing problem of minimizing the average number of copies of a message that satisfies the required delivery probability under the given time-to-live of the message as a nonlinear optimization problem. To solve this problem, we propose an improved genetic algorithm called genetic algorithm for delivery probability and time-to-live optimization for the dynamic quota-controlled routing scheme to reduce the routing cost further. In addition, a cost-efficient dynamic quota-controlled routing protocol based on genetic algorithm for delivery probability and time-to-live optimization is proposed, which can dynamically adjust message copies according to its assigned delivery probability and time-to-live in different communities on the shortest path. Both the numerical and simulation results show that our routing with the proposed algorithm is more cost efficient.

Revisiting Source Routing for Underwater Networking: The SUN Protocol

With respect to other routing paradigms, source routing has received comparatively less attention in the underwater acoustic networking domain. The most likely causes of this lack of momentum are the high overhead caused by route discovery and maintenance in typical implementations of the source routing paradigm (e.g., dynamic source routing) in terrestrial radio networks. In this paper, we revert this view and argue that source routing can in fact be a reliable and convenient routing paradigm in underwater networks, when properly implemented and tailored to the peculiarities of underwater acoustic channels. Our scheme, named SUN, successfully recasts the source routing approach by introducing a number of new features, which improve the routing performance especially in the presence of unstable network links and mobile nodes. SUN is scenario-independent by design: this means that it can work in any connected topology, and does not need any side information (such as the node location and depth, or the channel state) in order to operate correctly. We evaluate the performance of SUN by means of simulations using the DESERT Underwater framework. Our results show that SUN correctly manages routing in both static and mobile networks, and that in some scenarios it even achieves better performance than a competing flooding-based approach. We also test the performance of SUN in a thorough experimental campaign involving six nodes and carried out in a lake near Berlin. From these results, we conclude that SUN, and the source routing paradigm in general, are in fact feasible options for general-purpose routing in underwater acoustic networks.

Dynamic energy balanced max flow routing in energy-harvesting sensor networks

We propose a dynamic energy balanced max flow routing algorithm to maximize load flow within the network lifetime and balance energy consumption to prolong the network lifetime in an energy-harvest...

Routing in Wireless Networks With Interferences

We consider dynamic routing in multi-hop wireless networks with adversarial traffic. The model of wireless communication incorporates interferences caused by packets' arrivals into the same node that overlap in time. We consider two classes of adversaries: balanced and unbalanced. We demonstrate that, for each routing algorithm and an unbalanced adversary, the algorithm is unstable against this adversary in some networks. We develop a routing algorithm that has bounded packet latency against each balanced adversary.

Distributed Storage Control Algorithms for Dynamic Networks

Recent technological advances have rendered storage a readily available resource, yet there exist few examples that use it for enhancing network performance. We revisit in-network storage and we evaluate its usage as an additional degree of freedom in network optimization. We consider the network design problem of maximizing the volume of end-to-end transferred data and we derive storage allocation (placement) solutions. We show that different storage placements have different impact on the performance of the network and we introduce a systematic methodology for the derivation of the optimal one. Accordingly, we provide a framework for the joint optimization of routing and storage control (usage) in dynamic networks for the case of a single commodity transfer. The derived policies are based on time-expanded graphs and ensure maximum performance improvement with minimum possible storage usage. We also study the respective multiple commodity problem, where the network link capacities and node storage resources are shared by the different commodities. A key advantage of our methodology is that it employs algorithms that are applicable to both centralized as well as to distributed execution in an asynchronous fashion, and thus, no tight synchronization is required among the various involved storage and routing devices in an operational network. We also present an extensive performance evaluation study using the backbone topology and actual traffic traces from a large European Internet Service Provider, and a number of synthetic network topologies. Our results show that indeed our approach offers significant improvements in terms of delivery time and transferred traffic volume.

Investigation of dynamic routing and spectrum allocation methods in elastic optical networks

Abstract The introduction of flexible frequency grids and advanced modulation techniques to optical transmission, namely an elastic optical network, requires new routing and spectrum allocation techniques. In this paper, we investigate dynamic two-step routing and spectrum allocation (RSA) methods for elastic optical networks. K-shortest path-based methods as well as spectrum allocation methods are analysed and discussed. Experimental verification of the investigated techniques is provided using simulation software. Simulation results present effectiveness of routing and spectrum allocation methods for analyzed networks using requested bandwidth of connections. Moreover, performance of shortest path first methods improves considerably when a number of candidate paths increases in the UBN24 topology.

Trajectory-Adaptive Routing in Dynamic Networks with Dependent Random Link Travel Times

This paper addresses the problem of finding the optimal routing policies with only trajectory information in a stochastic time-dependent network where all link travel times are temporally and spatially correlated. Two equivalent definitions are given for trajectory-adaptive routing policy. The first definition follows the mapping definition in a series of previous studies, where the trajectory information is included in the state variable. With that definition, any subpolicy of an optimal routing policy must also be optimal, and the algorithm developed in previous studies could serve as an exact solution, but the nature of the definition that trajectory information is included in the state variable determines that the number of states is prohibitively huge. Therefore, a second definition is given as a recursive definition, where the trajectory information is not included in the state variable. It is shown that, with the second definition, a subpolicy of an optimal/nondominated routing policy is not necessarily optimal/nondominated, but any subpolicy of a pure routing policy must also be pure which is a new property defined based on nondominance. An exact algorithm is designed to find optimal trajectory-adaptive routing policies based on the aforementioned property of pure routing policy. A comparison is made between the optimal trajectory-adaptive routing policies and the optimal paths in the same test networks to investigate the benefit of being adaptive. The results show that the benefit of being adaptive to trajectory information is more significant with a higher risk aversion, a higher correlation, and/or a larger network. The online appendix is available at https://doi.org/10.1287/trsc.2016.0691 .

Quality of service aware fuzzy dynamic routing and wavelength assignment technique in all optical networks

In this paper, a novel fuzzy dynamic routing and wavelength assignment technique is proposed for a wavelength division multiplexing optical network to achieve the best quality of network transmission. This paper proposes a novel quality of service aware fuzzy logic controlled dynamic routing and wavelength assignment algorithm (QoS-FDRWA), where the optimum path is chosen by a fuzzy rule-based inference system. The proposed fuzzy routing technique incorporates optical network transmission attributes such as latency, physical length of the link, data packet loss, number of hops, and wavelength availability status in the path.

Distributed rate control, routing, and energy management in dynamic rechargeable sensor networks

This paper studies the network utility maximization (NUM) problem in dynamic-routing rechargeable sensor networks (RSNs), where rate control, routing, and energy management need to be jointly optimized. This problem is very challenging since the flow constraint is spatially coupled and the energy constraint is spatiotemporally coupled (energy causality). Existing works either do not fully consider the two coupled constraints together, or heuristically remove the temporally-coupled part, both of which are not practical, and may degrade network performance. In this paper, we attempt to jointly optimize rate control, routing, and energy management by carefully tackling the flow and energy constraints. To this end, we first decouple the original problem equivalently into separable subproblems by means of dual decomposition. Then, we propose a distributed algorithm, which can converge to the globally optimal solution. Numerical results based on real solar data are presented to evaluate the optimality and scalability of the proposed algorithm.

Mobile node aware opportunistic routing in dynamic wireless sensor network

Opportunistic routing (OR) could adapt to dynamic wireless sensor networks (WSNs) because of its inherent broadcast nature. Most of the existing OR protocols focus on the variations of propagation environment which are caused by channel fading. However, a few works deal with the dynamic scenario with mobile nodes. In this paper, a mobile node (MN) aware OR (MN-OR) is proposed and applied to a WSN in the high-speed railway scenario where the destination node is deployed inside a high speed moving train, and the MN-OR not only considers the mobility of node but also utilizes the candidate waiting time induced by the timer-based coordination scheme. Specifically, to reduce the number of duplicate transmissions and mitigate the delay of information transmission, a new selection strategy of the candidate forwarders is presented. In addition, two priority assignment methods of the candidate forwarders are proposed for the general relay nodes (GRNs) and the rail-side nodes (RSNs) according to their different routing requirements. Extensive simulation results demonstrate that the proposed MN-OR protocol can achieve better network performances compared with some existing routing schemes such as the well-known Ad-hoc on-demand distance vector routing (AODV) and the extremely opportunistic routing (ExOR) protocols.

Distributed optimization of lifetime and throughput with power consumption balance opportunistic routing in dynamic wireless sensor networks

This article studies a joint performance optimization on the network lifetime and network throughput for an energy-constrained dynamic wireless sensor network. We propose a fully distributed power consumption balance opportunistic routing scheme to cope with the dynamic network that is not considered in the classic low-energy adaptive clustering hierarchy routing and evenly allocate power consumption among the sensor nodes for obtaining longer network lifetime. Moreover, a fully distributed optimization solution, whose distinctive feature to the Lagrange dual approach is capable of handling the changing network, is developed to achieve joint performance optimization of objectives. We mathematically prove the convergence of the proposed solution and analyze its computational complexity. Extensive simulation results illustrate the effective measures to deal with the varying network of power consumption balance opportunistic routing and the best tradeoff performance achieved by the proposed solution and evaluate the more positive impact on the network lifetime of power consumption balance opportunistic routing than the existing routings and better ability to adapt the dynamic network of the proposed solution than the Lagrange dual approach.

A Dynamic Tracing Model for Agile Software Product Lines Domain Engineering from Features to Structural Elements: An Approach Based on Dynamic Routing

Even if the benefit of implementing Software Product Lines is well established, adopting such a large system is still a complex choice to make: it is hard to implement, needs a good knowledge of market growth and a clear vision of the enterprise objectives for long term. Therefore, many companies remain unwilling to adopt such an approach, unless they gain flexibility and get guarantees. Flexibility can be achieved by adopting an Agile Software Product Line approach, to make sure changes are rapidly implemented and product adapted to market evolution. Guarantees can be acquired by tracing elements and the relations between them. However, tracing in Agile Software Product Line context still needs to gain maturity as it is costly and therefore rarely adopted. In this paper, we discuss the added value of traceability for Agile Software Product Lines, and present our tracing model inspired from dynamic network routing.

An Efficient Route Maintenance Protocol for Dynamic Bluetooth Networks

Bluetooth is a widespread technology for small wireless networks that permits Bluetooth devices to construct a multi-hop network called scatternet. Routing in multi-hop dynamic Bluetooth network, where a number of masters and bridges exist creates technical hitches. It is observed that frequent link disconnections and a new route construction consume extra system resources that degrade the whole network performance. Therefore, in this paper an Efficient Route Maintenance Protocol for Dynamic Bluetooth Networks (ERMP) is proposed that repairs the weak routing paths based on the prediction of weak links and weak devices. The ERMP predicts the weak links through the signal strength and weak devices through low energy levels. During the main route construction, routing masters and bridges keep the information of the Fall Back Devices (FBDs) for route maintenance. On the prediction of a weak link, the ERMP activates an alternate link, on the other hand, for a weak device it activates the FBD. The proposed ERMP is compared with some existing closely related protocols, and the simulation results show that the proposed ERMP successfully recovers the weak paths and improves the system performance.

Graph-Model-Based Dynamic Routing and Spectrum Assignment in Elastic Optical Networks

In recent years, the concept of the elastic optical network (EON) was proposed and very quickly became an attractive solution for flexible channel bandwidth utilization. Analogous to the routing and wavelength assignment (RWA) problem in traditional wavelength-routed networks, routing and spectrum assignment (RSA) is the most basic and critical resource management issue in EONs. In this work, we exploit and modify the layered graph model, which is a well-known RWA model, to design two RSA heuristic algorithms named LG-FF and LG-SP. Additionally, we also derive an analytical model to estimate the number of required layered graphs. Numerical results demonstrate that LG-SP can achieve the same blocking performance level with significant time complexity reduction as compared to the near-optimal solution. Whether we care about blocking performance or aim at saving computational time, the layered graph is an important representation model of resource utilization status to efficiently solve the RSA problem.

Fairness enhanced dynamic routing and spectrum allocation in elastic optical networks

The finer spectrum granularity unit in elastic optical networks makes wider spectrum services more likely to be restricted by the constraints of spectrum continuity and spectrum contiguity (2SC), leading to higher blocking probability (BP). Obviously, it would deteriorate the fairness among multi-granularity services. Therefore, a fair dynamic routing and spectrum allocation algorithm is proposed. By virtualising the network resources as a ‘resource pool’, a two-dimensional rectangle packing model in combination with service holding-time is introduced to satisfy the 2SC constraints and to optimise the allocation of the ‘resource pool’ for dynamic multi-granularity services. Besides multi-granularity service fairness is achieved by tackling heterogeneous-size services together. Simulation results show that the benefit in terms of fairness can be reaped. Meanwhile, the authors also investigate the proposed algorithm's impact on performance metrics: namely, spectrum resource utilisation and BP. The results indicate that the proposed algorithm can achieve lower BP and higher spectrum efficiency.

Data Gathering Optimization by Dynamic Sensing and Routing in Rechargeable Sensor Networks

In rechargeable sensor networks (RSNs), energy harvested by sensors should be carefully allocated for data sensing and data transmission to optimize data gathering due to time-varying renewable energy arrival and limited battery capacity. Moreover, the dynamic feature of network topology should be taken into account, since it can affect the data transmission. In this paper, we strive to optimize data gathering in terms of network utility by jointly considering data sensing and data transmission. To this end, we design a data gathering optimization algorithm for dynamic sensing and routing (DoSR), which consists of two parts. In the first part, we design a balanced energy allocation scheme (BEAS) for each sensor to manage its energy use, which is proven to meet four requirements raised by practical scenarios. Then in the second part, we propose a distributed sensing rate and routing control (DSR2C) algorithm to jointly optimize data sensing and data transmission, while guaranteeing network fairness. In DSR2C, each sensor can adaptively adjust its transmit energy consumption during network operation according to the amount of available energy, and select the optimal sensing rate and routing, which can efficiently improve data gathering. Furthermore, since recomputing the optimal data sensing and routing strategies upon change of energy allocation will bring huge communications for information exchange and computation, we propose an improved BEAS to manage the energy allocation in the dynamic environments and a topology control scheme to reduce computational complexity. Extensive simulations are performed to demonstrate the efficiency of the proposed algorithms in comparison with existing algorithms.

Dynamic information routing in complex networks.

Flexible information routing fundamentally underlies the function of many biological and artificial networks. Yet, how such systems may specifically communicate and dynamically route information is not well understood. Here we identify a generic mechanism to route information on top of collective dynamical reference states in complex networks. Switching between collective dynamics induces flexible reorganization of information sharing and routing patterns, as quantified by delayed mutual information and transfer entropy measures between activities of a network's units. We demonstrate the power of this mechanism specifically for oscillatory dynamics and analyse how individual unit properties, the network topology and external inputs co-act to systematically organize information routing. For multi-scale, modular architectures, we resolve routing patterns at all levels. Interestingly, local interventions within one sub-network may remotely determine nonlocal network-wide communication. These results help understanding and designing information routing patterns across systems where collective dynamics co-occurs with a communication function.

Dynamic Capacity Routing in Networks with MTSP

Dynamic Capacity Routing in Networks with MTSP

A low energy adaptive clustering multi-hop routing protocol based on fuzzy decision

In large-scale wireless sensor networks, a low energy consumption requirement in data communication has become more prominent, but the currently existing solutions are unsatisfactory. Based on the complexity and uncertainty in the node energy consumption and communication path in wireless sensor networks, this paper proposes a low energy adaptive clustering multi-hop routing protocol based on fuzzy decision (FD-LEACH). In order to constitute a dynamic network routing structure, the protocol introduces the concept of fuzzy set and uses the theory of fuzzy decision to select excellent communication relay nodes. Analysis and simulation results demonstrate that the proposed protocol is more effectively adapted to large-scale wireless networks, which can provide a better balance in energy consumption and significantly prolong network lifetime.