ABSTRACT.Wireless sensor networks (WSN) are the subject of the era due to its importance and wide applications. The last decade of research focused on how to improve its performance in terms of enlarging lifetime and better handling network dynamics. Many WSN applications such as monitoring and reporting are time critical so, the performance of WSN can not include lifetime only, but also other performance measures such as delay must be taken into consideration as well. This paper focuses on the WSN network layer which includes routing techniques as a main key in high performance applications. A routing technique based on virtual rings and genetic algorithm is proposed to shorten the round delay time. This technique uses virtual ring features in addition to clustering methods to divide the sensors in the network into groups contain nearby sensors. The main advantage of this proposed technique is that it maximizes the interval of the first node failure besides obtaining a reasonable delay in forwarding data to sink through the usage of the virtual rings.

ABSTRACT.Wireless sensor networks (WSN) are the subject of the era due to its importance and wide applications. The last decade of research focused on how to improve its performance in terms of enlarging lifetime and better handling network dynamics. Many WSN applications such as monitoring and reporting are time critical so, the performance of WSN can not include lifetime only, but also other performance measures such as delay must be taken into consideration as well. This paper focuses on the WSN network layer which includes routing techniques as a main key in high performance applications. A routing technique based on virtual rings and genetic algorithm is proposed to shorten the round delay time. This technique uses virtual ring features in addition to clustering methods to divide the sensors in the network into groups contain nearby sensors. The main advantage of this proposed technique is that it maximizes the interval of the first node failure besides obtaining a reasonable delay in forwarding data to sink through the usage of the virtual rings.

In this paper, we present a modified on-demand routing algorithm for mobile ad-hoc networks (MANETs). The proposed algorithm is based on both the standard Ad-hoc On-demand Distance Vector (AODV) protocol and ant colony based optimization. The modified routing protocol is highly adaptive, efficient and scalable. The main goal in the design of the protocol was to reduce the routing overhead, response time, end-to-end delay and increase the performance. We refer to the new modified protocol as the Multi-Route AODV Ant routing algorithm (MRAA).

In this paper, we present a modified on-demand routing algorithm for mobile ad-hoc networks (MANETs). The proposed algorithm is based on both the standard Ad-hoc On-demand Distance Vector (AODV) protocol and ant colony based optimization. The modified routing protocol is highly adaptive, efficient and scalable. The main goal in the design of the protocol was to reduce the routing overhead, response time, end-to-end delay and increase the performance. We refer to the new modified protocol as the Multi-Route AODV Ant routing algorithm (MRAA).

In this paper, we present a modified on-demand routing algorithm for mobile ad-hoc networks (MANETs). The proposed algorithm is based on both the standard Ad-hoc On-demand Distance Vector (AODV) protocol and ant colony based optimization. The modified routing protocol is highly adaptive, efficient and scalable. The main goal in the design of the protocol was to reduce the routing overhead, response time, end-to-end delay and increase the performance. We refer to the new modified protocol as the Multi-Route AODV Ant routing algorithm (MRAA).

In this paper, we propose two methods to improve the Ad-Hoc On-Demand Distance-Vector (AODV) protocol. The main goal in the design of the protocol was to reduce the routing overhead, buffer overflow, end-to-end delay and increase the performance. A multi-path routing protocol is proposed which is based on AODV and Ant Colony Optimization (ACO). This protocol is refereed to Multi-Route AODV Ant routing (MRAA). Also we propose a load balancing method that uses all discovered paths simultaneously for transmitting data. In this method, data packets are balanced over discovered paths and energy consumption is distributed across many nodes through network. This protocol is refereed to Load Balanced Multi-Route AODV Ant routing algorithm (LBMRAA).

In this paper, we propose two methods to improve the Ad-Hoc On-Demand Distance-Vector (AODV) protocol. The main goal in the design of the protocol was to reduce the routing overhead, buffer overflow, end-to-end delay and increase the performance. A multi-path routing protocol is proposed which is based on AODV and Ant Colony Optimization (ACO). This protocol is refereed to Multi-Route AODV Ant routing (MRAA). Also we propose a load balancing method that uses all discovered paths simultaneously for transmitting data. In this method, data packets are balanced over discovered paths and energy consumption is distributed across many nodes through network. This protocol is refereed to Load Balanced Multi-Route AODV Ant routing algorithm (LBMRAA).

In this paper, we propose two methods to improve the Ad-Hoc On-Demand Distance-Vector (AODV) protocol. The main goal in the design of the protocol was to reduce the routing overhead, buffer overflow, end-to-end delay and increase the performance. A multi-path routing protocol is proposed which is based on AODV and Ant Colony Optimization (ACO). This protocol is refereed to Multi-Route AODV Ant routing (MRAA). Also we propose a load balancing method that uses all discovered paths simultaneously for transmitting data. In this method, data packets are balanced over discovered paths and energy consumption is distributed across many nodes through network. This protocol is refereed to Load Balanced Multi-Route AODV Ant routing algorithm (LBMRAA).

In this paper, we propose two methods to improve the Ad-Hoc On-Demand Distance-Vector (AODV) protocol. The main goal in the design of the protocol was to reduce the routing overhead, buffer overflow, end-to-end delay and increase the performance. A multi-path routing protocol is proposed which is based on AODV and Ant Colony Optimization (ACO). This protocol is refereed to Multi-Route AODV Ant routing (MRAA). Also we propose a load balancing method that uses all discovered paths simultaneously for transmitting data. In this method, data packets are balanced over discovered paths and energy consumption is distributed across many nodes through network. This protocol is refereed to Load Balanced Multi-Route AODV Ant routing algorithm (LBMRAA).

Working with the DUC 2002 collection for multi-document summarization, we considered two types of document sets: sets consisting of closely correlated documents with highly overlapped content; and sets of diverse documents covering a wide scope of topics. Intuitively, this suggests that creating a quality summary would be more difficult for the latter case. The two types of document sets can be identified automatically by our document graph approach. However, human evaluators were shown to be fairly insensitive to this difference. This was identified when they were asked to rank the performance of automated summarizers. In this paper, we examine and analyze our experiment in order to better understand this phenomenon and how we might address it to improve summarization.