Chotipat Pornavalai

An adaptive alert message dissemination protocol for VANET to improve road safety

Vehicular Ad-hoc Network (VANET) is gaining much attention recently because of its many important applications in transportation, to improve road safety, reduce traffic congestion, to enable efficient traffic management etc. However, there are several technical issues to be addressed for its effective deployment. Stability in communication in VANET is difficult to achieve due to rapid network changes. Restoration is inefficient while using traditional protocols based on broadcast storm. In this paper, we propose a new adaptive protocol to improve performance for on road safety alert application in VANET. It can alleviate the broadcast storm problem using adaptive wait-windows and adaptive probability to transmit. Simulation shows that our proposed approach has better performances in terms of number of collision, success rate, and delay, when compared with other existing protocols.

A neural network approach to multicast routing in real-time communication networks

Real-time communication networks are designed mainly to support multimedia applications, especially the interactive ones, which require a guarantee of Quality of Service (QoS). Moreover, multicasting is needed as there are usually more than two peers who communicate together using multimedia applications. As for the routing, the network has to find an optimum (least cost) multicast route, that has enough resources to provide or guarantee the required QoS. This problem is called QoS constrained multicast routing and was proved to be an NP-complete problem. In contrast to the existing heuristic approaches, in this paper we propose a modified version of a Hopfield neural network model to solve QoS (delay) constrained multicast routing. By the massive parallel computation of neural networks, it can find a near optimal multicast route very fast, when implemented in hardware. Simulation results show that the proposed model has performance near to the optimal solution and comparable to existing heuristics.

Fuzzy-Spray: Efficient routing in delay tolerant ad-hoc network based on fuzzy decision mechanism

Delay Tolerant Network (DTN) is a sparse and intermittently connected mobile wireless network where reliable communication and end-to-end connectivity cannot be assured. In DTN, a node delivers messages to the destination using store and forward scheme. Messages are copied and transferred to multiple relay-nodes in order to increase the opportunity for that message to reach the intended destination. Contact is the time duration for which two or more mobile nodes encounter each other within their radio transmission ranges, and are able to transfer messages. Due to arbitrary node movement, contact time will be varied, and is unlikely to be predictable. In this paper, we propose a fuzzy decision mechanism we called “fuzzy-spray”, to improve the routing and packet transfer efficiency in DTN environment. Fuzzy-spray can reduce overall latency in DTN by intelligently selecting appropriate messages to send to the relay-node during its next contact time. It uses fuzzy logic to prioritize messages that are stored in the buffer, based only on local parameters from each message, namely forward transmission count and message size. There is no need to know a priori information about network such as node mobility model, or node-distribution across the deployed area. The simulation results show that fuzzy-spray has the best performance in terms of overall speed of delivery, and lowest average message delay compared with other existing algorithms.

Routing with multiple QoS requirements for supporting multimedia applications

Distributed multimedia applications usually require multiple QoS performance guarantees. However, in general, searching such a route in the network, to support multimedia applications, is known to be NP‐complete. In this paper, we propose a new heuristic QoS routing algorithm, called “QoSRDKS”, for supporting multimedia applications in high‐speed networks. QoSRDKS is a modification of rule‐based Fallback routing and Dijkstra algorithms. It can search a unicast route that would have enough network resources so that multiple QoS requirements (bandwidth, delay, and delay jitter) of the requested flow could be guaranteed. Its worst case computation time complexity is the same as that of the Dijkstra algorithm, i.e., O(❘V❘2), where ❘V❘ is the number of nodes in the network. Extensive simulations were done with various network sizes, upto 500 nodes networks, where each node uses Weighted Fair Queueing (WFQ) service discipline. Results show that QoSRDKS is very efficient. It could always find the QoS satisfying route, whenever there exists one (success rate is optimal), and its average computation time is near to simple shortest path Dijkstra algorithm.

Optimal Routing for Dynamic Multipoint Connection

Multimedia applications are becoming increasingly important as networks are now capable to carry continuous media traffic, such as voice and video, to the end user. Most of the multimedia applications need multicast support too. In dynamic multicasting, destination nodes can join and leave the group during the communication period. Total or partial rerouting can optimize the tree cost to some extent. But rerouting for optimization is complex as cell-ordering at ATM switches has to be preserved. Optimum Steiner tree is NP-complete and therefore the present problem too. We propose a heuristic centralized routing algorithm, which optimize the total cost of the Steiner tree over the whole session period, where information about the joining and leaving of participants are available, at the time s/he actually joins. With this algorithm, the average hop-length from source to destination has also reduced considerably. The efficiency of our algorithm and comparison with other proposed algorithms is shown by various simulation results.

A light-weight fault-tolerant time synchronization for wireless sensor networks

Wireless sensor networks (WSN) have received a lot of attention recently due to their enormous potential in different applications. Many applications in WSN require time synchronization among all the sensor nodes. However, in practice, network do normally have some abnormal nodes (we called Fault Clock Node or FCN), which could cause high synchronization error. In this paper, we present a light-weight fault-tolerant time synchronization protocol (LiFTiS) which works in a way similar to NTP. The protocol is aware of FCN and is able to detect its children in hierarchical tree. We also propose a light-weight algorithm for selecting the best parent. Our simulation results show that the average synchronization error using the proposed protocol is 5-31% less than the existing algorithms e.g. TPSN etc.

Neural networks for solving constrained Steiner tree problem

A Hopfield neural network model for finding an optimal or shortest path between two nodes in a graph was proposed recently in some literature. In this paper, the authors present a modified version of the Hopfield model to find an optimal tree (least total cost tree) from a source node to a number of destination nodes, where each path from source to a destination must satisfy a constraint condition (delay bound condition). This problem is called the constrained Steiner tree (CST) problem, and was proved to be NP-complete. A new adaptive coefficient control method for the proposed Hopfield energy function is also developed. Through computer simulation it is shown that the proposed model could always find a near-optimal valid solution.

Neural network for optimal Steiner tree computation

Hopfield neural network model for finding the shortest path between two nodes in a graph was proposed recently in some literatures. In this paper, we present a modified version of Hopfield model to a more general problem of searching an optimal tree (least total cost tree) from a source node to a number of destination nodes in a graph. This problem is called Steiner tree in graph theory, where it is proved to be a NP-complete. Through computer simulations, it is shown that the proposed model could always find an optimal or near-optimal valid solution in various graphs.

Adaptive multi-hop routing for wireless sensor networks

A large portion of energy-aware routing protocol for wireless sensor networks are cluster-based. In cluster based approach, energy at the cluster head nodes are drained more rapidly compared to other member nodes. Dynamically change cluster heads periodically could partialy mitigate this problem, but clusters that are far from base station still suffer from large amount of energy for directly transmit their cluster data back to base station. Multi-hop routing was introduced to reduce energy dissipation of cluster heads that far away from base station by relaying data through nearer cluster heads. However it may overload cluster heads that are near the base station. In this paper, we propose an adaptive multi-hop hierarchical routing approach where member nodes in cluster may send their data, based on distance information, to cluster head or to base station directly to reduce energy dissipation of cluster heads. This decision is independent at each node which makes this approach highly distributed. Simulation results show that the proposed routing protocol has longer node lifetime than the original LEACH and M-LEACH protocol.

Dynamic multicast routing in advance resource reservation environment

Since network resources are usually limited, the ability to carry out resource reservation in advance, as well as efficient dynamic multicasting when destination nodes can join and leave the group during the communication period, are essential in all distributed multi-party applications. Total or partial re-routing of a multicast tree for dynamic multicast groups can optimize the tree cost to some extent but they are complex. Furthermore, optimal multicast routing has been proved to be an NP-complete problem. In this paper, we propose an efficient dynamic multicast routing algorithm, which optimizes the total cost of the Steiner tree over the whole session period in an advance resource reservation environment, where information about the resource reservation (i.e. leaving times of participants at the time of joining) are available. The efficiency of our algorithm compared to other existing algorithms is shown by various simulation results.