Data Grid allows many organizations to share data across large geographical area. The idea behind data replication is to store copies of the same file at different locations. Therefore, if a copy at a location is lost or not available, it can be brought from another location. Additionally, data replication results in a reduced time and bandwidth because of bringing the file from a closer location. However, the files that need to be replicated have to be selected wisely. In this paper, a round-based data replication strategy is proposed to select the most appropriate files for replication at the end of each round based on a number of factors. The proposed strategy is based on Popular File Replicate First (PFRF) strategy, and it overcomes the drawbacks of PFRF. The simulation results show that the proposed strategy yields better performance in terms of average file delay per request, average file bandwidth consumption per request, and percentage of files found.

A sensing-covered network is a wireless sensor network where every single point in the geographic area is covered by the sensing range of at least one sensor node. For routing on such a 2-Dsensing-covered network topology, we propose a new greedy forwarding-type progress-based routing protocolGC2, as well as a hybrid routing algorithmSCL:GC2which is based onGC2and a faster simplified version of theBVGFrouting protocol of Xing et al (2006), called SCL. Both these algorithms guarantee delivery on sensing-covered networks, even when the average node degree is reduced by routing on an Adaptive Yao subgraph. We demonstrate through simulations thatGC2improves on the performance of greedy forwarding, and thatSCL:GC2finds paths with average lengths that are close to those forBVGFwhile performing significantly fewer expensive calculations.

Numerous routing algorithms have been proposed for routing efficiently in mobile ad hoc networks (MANETs) embedded in two dimensional (2D) spaces. But, in practice, such networks are frequently arranged in three dimensional (3D) spaces where the assumptions made in two dimensions, such as the ability to extract a planar subgraph, break down. Recently, a new category of 3D position-based routing algorithms based on projecting the 3D MANET to a projection plane has been proposed. In particular, the adaptive least-squares projective (ALSP) face routing algorithm (Kao et al., 2007) achieves nearly guaranteed delivery but usually discovers excessively long routes to the destination. Referencing the idea of hybrid greedy-face-greedy (GFG) routing in 2D MANETs, we propose a local hybrid algorithm combining greedy routing with ALSP Face routing on projection planes. We show experimentally that this hybrid ALSP GFG routing algorithm on static 3D ad hoc networks can achieve nearly guaranteed delivery while discovering routes significantly closer in length to shortest paths. The mobility of nodes is handled by introducing the concepts of active sole nodes and a limited form of flooding called residual path finding to the ALSP GFG routing algorithm. Under mobility simulations, we demonstrate that the mobility-adapted hybrid routing algorithm can maintain high delivery rates with decreases in the average lengths of the paths discovered compared to shortest paths, without generating a large amount of flooding traffic.

A crucial problem in ad hoc networks is finding an efficient and correct route between a source and a destination; however for many networks, a more important problem is providing an energy efficient route because of, for example, the limited battery life of the wireless nodes. Most previous routing protocols make the routing decision without taking into account the energy budget of the nodes. In addition, when using a fixed transmission power, nodes may waste power by transmitting with more power than is needed for correct reception. In position- based routing algorithms, the nodes use the geographical position of the nodes to make the routing decisions. In this paper we present several localized power-aware 3D position-based routing algorithms that increase the life-time of the network by maximizing the life time of the nodes. These new algorithms use the idea of replacing the constant transmission power of the node with an adjusted transmission power during two stages - first a lower power while discovering the neighboring nodes, and, if needed, a second higher transmission power during the routing process. We evaluate our algorithms and compare their power savings with the current power-aware routing algorithms. The simulation results show a significant improvement in the energy saving (up to 50%).

In position-based routing algorithms for ad-hoc networks, the nodes use the geographical information to make the routing decisions. Recent research in this field primarily addresses such routing algorithms in two dimensional space (2D). However, in real applications, nodes may be distributed in 3D space. In this paper we extend previous randomized routing algorithms from 2D space to 3D space, and we propose two new position-based routing algorithms that combine randomized AB3D routing algorithms with a deterministic CFace (coordinate face) algorithm. The first algorithm AB3D-CFace(I)-AB3D starts with AB3D routing algorithm until a local minimum is reached. The algorithm then switches to CFace routing using one projected coordinate. IfCFace(I) enters a loop, the algorithm switches back to AB3D. The second algorithm AB3D-CFace(3) starts with AB3D, until a local minimum is reached. The algorithm then permanently switches to CFace routing using three projected coordinates, in order. We evaluate our mechanisms and compare them with the current routing algorithms. The simulation results show the significant improvement in delivery rate over pure AB3D randomized routing (97% compared to 70%) and reduction in path dilation (up to 50%) over pure CFace algorithm