Service-based Routing Research Articles

Innovating R Tree for Message Forwarding Technique and Hierarchical Network Clustering in Service Based Routing

In service based routing (SBR) [5], the problem for storing forwarding table that includes searching predicates received from subscribers through subscription messages is an important job. When a content request happens, the subscriber will create a subscription message. The subscription message stores several kinds of information, the most important content is a filter that is a conjunction of some constraints [5]. A filter is denoted by F character, that has mathematical formula: F = ⋀n i=1C1, in which C1 is service request, has the format: C1= ‘Service_name = requested service name’. Every C1 (i=¯(2..n)) is a constraint that is formed by three components: (Key, op, Value), Key is a keyword for searching, op is an operator, Value is searching condition. Key belongs to the set of name of properties of content messages that the requested service supplies. Op is an operator that depends on the type of data of the Key. Therefore the forwarding table is a set of filters which are received from all subscribers on networks. The algorithms for inserting, updating, deleting and finding filters that match content messages have been published by service providers are very important. In this paper, We mention a technique for forwarding technique on the basic of summary filter for storing and searching filter quickly. This technique is based on some previous researches. In section 8, give an algorithm for finding all network nodes that have matched filters with a content message. Section 7 introduces a cluster routing technique based on summary filter.

Research on Innovating and Applying Evolutionary Algorithms Based Hierarchical Clustering and Multiple Paths Routing for Guaranteed Quality of Service on Service Based Routing

In Service Based Routing (SBR), data is transmitted from a source node to destination nodes are not depended on destination addresses. Hence, it is comfortable with new advanced technology as cloud computing and also flexible and reliable. Genetic and Queen-Bee algorithms (GA, QB) are artificial intelligence techniques for combinatorial optimization problems solving based on some natural rules. In which GA is a branch of the evolutionary strategies that uses some principles of evolution theory, such as natural selection, mutation and crossover. QB is performed based on GA for energy saving. The R^+ tree is an effective data structure that can be used to organize a hierarchical clustering network with fast establishing, updating, tuning algorithms. The usage of the Greedy algorithm to find cyclic routes or multiple paths on each trunk by multiple criterions to transmit data effectively.

Building Multile Multicast Trees with Guarranteed QOS for Service Based Routing Using Artificial Algorithms

In Service Based Routing (SBR), data is transmitted from a source node to destination nodes are not depended on destination addresses. Hence, it is comfortable with new advanced technology as cloud computing and also flexible and reliable. Multicast routing is advanced technique to deliver data simultaneously from one source node to multiple destination nodes with QOS (quality of service). In this paper, we introduce a technique that is extended from multicast technique with multiple multicast trees that are conformed quality of service routing. This technique is based on Greedy, Ant Colony Optimization, and fuzzy logic to get optimal routes to transmit data from one source to multiple destination node very effectively. The usage of the ANT Colony optimization, Greedy, fuzzy logic algorithms to find cyclic or multiple paths routes on each trunk by multiple criterions to transmit data effectively.

Innovating Multicast Tree and Artificial Algorithms for Service Based Routing

In advance network we may use service Based Routing (SBR), so data is transmitted from a source node to destination nodes are not depended on destination addresses. So, it may be comfortable with new advanced technology as cloud computing and also flexible and reliable. Multicast routing is advanced technique to deliver data simultaneously from one source node to multiple destination nodes with QOS (quality of service). In this paper, we introduce a technique that is extended from multicast technique with multiple multicast trees that are conformed quality of service routing and multiple path routing. It also guarantees QOS of routes such as bandwidth. This technique is based on Greedy, Ant Colony Optimization, artificial neural network and fuzzy logic to get optimal routes to transmit data from one source to multiple destination node very effectively. The usage of the ANT Colony optimization, Greedy, fuzzy logic algorithms to find cyclic or multiple paths routes on each trunk by multiple criterions to transmit data effectively.

An Analysis of Incentives for Network Infrastructure Investment Under Different Pricing Strategies

The Internet is making a significant transition from primarily a network of desktop computers to a network variety of connected information devices such as personal digital assistants and global positioning system-based devices. On the other hand, new paradigms such as overlay networks are defining service-based logical architecture for the network services that make locating content and routing more efficient. Along with Internet2's proposed service-based routing, overlay networks will create a new set of challenges in the provision and management of content over the network. However, a lack of proper infrastructure investment incentive may lead to an environment where network growth may not keep pace with the service requirements. In this paper, we present an analysis of investment incentives for network infrastructure owners under two different pricing strategies: congestion-based negative externality pricing and the prevalent flat-rate pricing. We develop a theoretically motivated gradient-based heuristic to compute maximum capacity that a network provider will be willing to invest in under different pricing schemes. The heuristic appropriates different capacities to different network components based on demand for these components. We then use a simulation model to compare the impact of dynamic congestion-based pricing with flat-rate pricing on the choice of capacity level by the infrastructure provider. The simulation model implements the heuristic and ensures that near-optimal level of capacity is allocated to each network component by checking theoretical optimality conditions. We investigate the impact of a variety of factors, including the per unit cost of capacity of a network resource, average value of the users' requests, average level of users' tolerance for delay, and the level of exogenous demand for services on the network. Our results indicate that relationships between these factors are crucial in determining which of the two pricing schemes results in a higher level of socially optimal network capacity. The simulation results provide a possible explanation for the evolution of the Internet pricing from time-based to flat-rate pricing. The results also indicate that regardless of how these factors are related, the average stream of the net benefits realized under congestion-based pricing tends to be higher than the average net benefits realized under flat-rate pricing. These central results point to the fallacy of the arguments presented by the supporters of net neutrality that do not consider the incentives for private investment in network capacity.

Energy-aware and quality of service-based routing in wireless sensor networks and vehicular ad hoc networks

Wireless Sensor Networks (WSNs) have increasingly been used for remote monitoring tasks. Limited capabilities of sensor nodes in terms of communication, computation, and storage, present challenges to protocols designed for WSNs. Due to the severe energy constraint of sensor nodes, among the major concerns is the problem of designing efficient energy-aware routing protocols. Numerous routing protocols have been proposed in the literature. Cluster-based routing protocols for large-scale WSNs have some advantages as compared to a flat network topology. Clustering results in a reduced number of messages that propagate through the network in order to accomplish a sensing task. It also offers improved power control. Quality of Service (QoS) is becoming an important feature of data routing in WSNs. QoS is required for real-time data transmission when the result of a sensing task is dependent not only on the correct sensing of the environment but also on the timely delivery of the event notification to the monitoring center, the Sink. The emergency preparedness and response class of applications, for instance, impose delay requirements on the delivery of event notification messages. Transmitting video and imaging data poses certain bandwidth, delay, and jitter requirements on the routing protocols. Vehicular Ad Hoc Networks (VANETs) are envisioned to improve intervehicle coordination and become a part of intelligent transport systems with an ultimate goal of increasing safety on the roads and improving travel comfort. VANETs may include WSNs that are placed along the sides of roads and provide monitoring of road conditions. Routing protocols for VANETs also aim at satisfying end-to-end QoS requirements. This paper first discusses energy-efficient clustering routing protocols for WSNs, followed by approaches aimed at satisfying QoS in WSNs and VANETS. Lastly, a discussion and comparison of features of the selected routing protocols and QoS-based approaches is presented.

Adaptive quality of service-based routing approaches: development of neuro-dynamic state-dependent reinforcement learning algorithms

In this paper, we propose two adaptive routing algorithms based on reinforcement learning. In the first algorithm, we have used a neural network to approximate the reinforcement signal, allowing th...