Optimal Shortest Path Routing Research Articles

PEDTARA: Priority-Based Energy Efficient, Delay and Temperature Aware Routing Algorithm Using Multi-Objective Genetic Chaotic Spider Monkey Optimization for Critical Data Transmission in WBANs

Software-Defined Wireless Body Area Network (WBAN)s have gained significance in emergency healthcare applications for remote patients. Prioritization of healthcare data traffic has a high influence on the congestion and delay in the WBAN routing process. Currently, the energy constraints, packet loss, retransmission delay and increased sensor heat are pivotal research challenges in WBAN. These challenges also degrade the network lifetime and create serious issues for critical health data transmission. In this context, a Priority-based Energy-efficient, Delay and Temperature Aware Routing Algorithm (PEDTARA) is presented in this paper using a hybrid optimization algorithm of Multi-objective Genetic Chaotic Spider Monkey Optimization (MGCSMO). This proposed optimized routing algorithm is designed by incorporating the benefits of chaotic and genetic operators to the position updating function of enhanced Spider Monkey Optimization. For the prioritized routing process, initially, the patient data transmission in the WBAN is categorized into normal, on-demand and emergency data transmissions. Each category is ensured with efficient routing using the three different strategies of the suggested PEDTARA. PEDTARA performs optimal shortest path routing for normal data, energy-efficient emergency routing for high priority critical data and faster but priority verified routing for on-demand data. Thus, the proposed PEDTARA ensures energy-efficient, congestion-controlled and delay and temperature aware routing at any given period of health monitoring. Experiments were performed over a high-performance simulation scenario and the evaluation results showed that the proposed PEDTARA performs efficient routing better than the traditional approaches in terms of energy, temperature, delay, congestion and network lifetime.

Toward Optimal Adaptive Online Shortest Path Routing With Acceleration Under Jamming Attack

We consider the online shortest path routing (SPR) of a network with stochastically time varying link states under potential adversarial attacks. Due to the denial of service (DoS) attacks, the distributions of link states could be stochastic (benign) or adversarial at different temporal and spatial locations. Without any a priori , designing an adaptive and optimal DoS-proof SPR protocol to thwart all possible adversarial attacks is a very challenging issue. In this paper, we present the first such integral solution based on the multi-armed bandit (MAB) theory, where jamming is the adversarial strategy. By introducing a novel control parameter into the exploration phase for each link, a martingale inequality is applied in our formulated combinatorial adversarial MAB framework. The proposed algorithm could automatically detect the specific jammed and un-jammed links within a unified framework. As a result, the adaptive online SPR strategies with near-optimal learning performance in all possible regimes are obtained. Moreover, we propose the accelerated algorithms by multi-path route probing and cooperative learning among multiple sources , and study their implementation issues. Comparing to existing works, our algorithm has the respective 30.3% and 87.1% improvements of network delay for oblivious jamming and adaptive jamming given a typical learning period and a 81.5% improvement of learning duration under a specified network delay on average, while it enjoys almost the same performance without jamming. Lastly, the accelerated algorithms can achieve a maximal of 150.2% improvement in network delay and a 431.3% improvement in learning duration.

Higher dimensional Eisenstein–Jacobi networks

An efficient interconnection topology called Eisenstein–Jacobi (EJ) network has been proposed in Martínez et al. (2008). In this paper this concept is generalized to higher dimensions. Important properties such as distance distribution and the decomposition of higher dimensional EJ networks into edge-disjoint Hamiltonian cycles are explored in this paper. In addition, an optimal shortest path routing algorithm and a one-to-all broadcast algorithm for higher dimensional EJ networks are given. Further, we give comparisons between higher EJ networks and Generalized Hypercube (GHC) networks and we show that higher EJ networks cost less and have more nodes than GHC networks.

Higher Dimensional Gaussian Networks

Gaussian interconnection networks have been introduced as a useful alternative to the classical toroidal networks, and in this paper this concept is generalized to higher dimensions. We also explore many important properties of this new topology, including distance distribution and the decomposition of higher dimensional Gaussian networks into edge-disjoint tori and Hamiltonian cycles. In addition, an optimal shortest path routing algorithm and a one-to-all broadcast algorithm for higher dimensional Gaussian networks are given. Simulation results show that the routing algorithm proposed for higher dimensional Gaussian networks outperforms the routing algorithm of the corresponding torus network of the same node-degree and the same number of nodes.

Exploiting generalized de-Bruijn/Kautz topologies for flexible iterative channel code decoder architectures

Modern iterative channel code decoder architectures have tight constrains on the throughput but require flexibility to support different modes and standards. Unfortunately, flexibility often comes at the expense of increasing the number of clock cycles required to complete the decoding of a data-frame, thus reducing the sustained throughput. The Network-on-Chip (NoC) paradigm is an interesting option to achieve flexibility, but several design choices, including the topology and the routing algorithm, can affect the decoder throughput. In this work logarithmic diameter topologies, in particular generalized de-Bruijn and Kautz topologies, are addressed as possible solutions to achieve both flexible and high throughput architectures for iterative channel code decoding. In particular, this work shows that the optimal shortest-path routing algorithm for these topologies, that is still available in the open literature, can be efficiently implemented resorting to a very simple circuit. Experimental results show that the proposed architecture features a reduction of about 14% and 10% for area and power consumption respectively, with respect to a previous shortest-path routing-table-based design.

GATEway: symbiotic inter-domain traffic engineering

There are a group of problems in networking that can most naturally be described as optimization problems (network design, traffic engineering, etc.). There has been a great deal of research devoted to solving these problems, but this research has been concentrated on intra-domain problems where one network operator has complete information and control. An emerging field is inter-domain engineering, for instance, traffic engineering between large autonomous networks. Extending intra-domain optimization techniques to inter-domain problems is often impossible without the information available within a domain, and providers are often unwilling to share such information. This paper presents an alternative: we propose a method for traffic engineering that does not require sharing of important information across domains. The method extends the idea of genetic algorithms to allow symbiotic evolution between two parties. Both parties may improve their performance without revealing their data, other than what would be easily observed in any case. We show the method provides large reductions in network congestion, close to the optimal shortest path routing across a pair of networks. The results are highly robust to measurement noise, the method is very flexible, and it can be applied using existing routing.

The k‐degree Cayley graph and its topological properties

AbstractThis article introduces a new family of Cayley graphs, called k‐degree Cayley graphs, for building interconnection networks. The k‐degree Cayley graph possesses many valuable topological properties, such as regularity with degree k, logarithmic diameter, and maximal fault tolerance. We present an optimal shortest path routing algorithm for the k‐degree Cayley graph. Cycle‐embedding and clique‐embedding are also discussed. © 2005 Wiley Periodicals, Inc. NETWORKS, Vol. 47(1), 26–36 2006

Optimal routing in shortest-path data networks

In this paper we address the problem of optimal routing in shortest-path data networks — such as Internet protocol (IP) networks — using open shortest path first (OSPF), routing information protocol (RIP), and other interior gateway protocols (IGPs). We propose a combinatorial algorithm for solving the optimal shortest-path routing problem, which consists of finding the link-distance metric assignment to all links in a network that results in optimal shortest-path routing and minimizes the average delay of packets in the network. Minimizing the delay of packets is critical, especially in the emerging voice over IP (VoIP) networks, quality of service (QoS)-centric virtual private networks (VPNs), and networks carrying other delay-sensitive traffic flows. Finding optimal link metrics that result in shortest-path routing is a special case of a classical inverse shortest-path problem. We propose a combinatorial approximation algorithm and illustrate the effectiveness of the proposed algorithm by comparing the results with bounds for several data network instances. We investigate not only the sensitivity of the solution with respect to the starting point, but also the sensitivity of the algorithm's performance with respect to uncertainty in traffic. We show that one preferred starting point consistently converges to near-optimal solutions. In addition, we extract two other distance metrics from the solution to the optimal general routing problem and show that these are preferred starting points for small or sparsely connected networks.

Comments on "An optimal shortest-path routing policy for network computers with regular mesh-connected topologies"

S. Badr and P. Podar (1989) introduced a zig-zag routing policy and showed its optimality for shortest-path routing on square or infinite grid networks with independent link failures. This paper shows that, contrary to the claim of Badr and Podar, a zig-zag policy is not optimal for shortest-path routing on torus networks.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

An optimal shortest-path routing policy for network computers with regular mesh-connected topologies

A probabilistic routing policy, the Z/sup 2/ (zigzag) routing policy, is presented within the class of nonadaptive, shortest-path routing policies for regular mesh-connected topologies such as n-dimensional toroids and hypercubes. The focus of the research is routing in networks of computers in a distributed computing environment, where constituent subcomputers are organized in a mesh-connected topology and communication among individual computers takes places by some form of message exchange. The authors prove the optimality of this policy with respect to two criteria: (1) maximizing the probability of reaching the destination from a given source without delays at intermediate nodes; and (2) minimizing the expected lifetime of a message.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>