Hot service deployment in an ad hoc grid environment

2004 ◽  
Author(s):  
Thomas Friese ◽  
Matthew Smith ◽  
Bernd Freisleben
Keyword(s):  
Ad Hoc ◽  
Grid Environment ◽  
Service Deployment

scholarly journals Interpretation on Energy Consumption of DYMO Protocol Towards Green Environment

2020 ◽  
Vol 9 (4) ◽  
pp. 2895-2897
Keyword(s):  
Energy Consumption ◽  
Ad Hoc Network ◽  
Ad Hoc ◽  
Mobile Ad Hoc Network ◽  
Mobile Nodes ◽  
Grid Environment ◽  
Data Packets ◽  
Dynamic Movement ◽  
Mobile Ad Hoc ◽  
Expensive Process

Mobile Ad hoc Network is a decentralized network which can be deployed instantly. Routing is a very challenging task in this network due to dynamic movement of mobile nodes. Various routing protocols such as OLSR, DYMO and ZRP are proposed to establish the route for the data packets in MANET’s. As deploying of the protocols into real environment is a cost expensive process, the protocols are initially evaluated through a simulated arena. Many of the mobile devices are battery equipped and each protocol consumes energy in different manner. In this paper, energy consumption evaluation is carried out on OLSR, DYMO and ZRP protocols in a grid environment. The experiments have shown that DYMO protocol has less energy consumption when compared to OLSR and ZRP protocols.

Performance Evaluation of Reactive Routing in Mobile Grid Environment

2011 ◽  
Vol 3 (3) ◽  
pp. 45-53 ◽  
Author(s):  
L. Shrivastava ◽  
G. S. Tomar ◽  
S. S. Bhadauria
Keyword(s):  
Grid Computing ◽  
Resource Sharing ◽  
Ad Hoc ◽  
Multicast Routing ◽  
Delivery Ratio ◽  
Grid Environment ◽  
On Demand ◽  
Reactive Routing ◽  
Grid Topology ◽  
Mathematical Problems

Grid computing came into existence as a manner of sharing heavy computational loads among multiple computers to be able to compute highly complex mathematical problems. The grid topology is highly flexible and easily scalable, allowing users to join and leave the grid without the hassle of time and resource-hungry identification procedures, having to adjust their devices or install additional software. The goal of grid computing is described as “to provide flexible, secure and coordinated resource sharing among dynamic collections of individuals, institutions and resources”. AODV is an on-demand (reactive) algorithm capable of both unicast and multicast routing. In this paper, AODV has been modified by varying some of the configuration parameters used in this algorithm to improve its performance. This modified protocol i.e. A-AODV (advanced ad hoc on demand distance vector) has been compared with AODV in grid environment. The simulations have shown that A-AODV is able to achieve high throughput and packet delivery ratio and average end-to-end delay is reduced.

Performance Evaluation of Reactive Routing in Mobile Grid Environment

2013 ◽  
pp. 159-167
Author(s):  
L. Shrivastava ◽  
G. S. Tomar ◽  
S. S. Bhadauria
Keyword(s):  
Grid Computing ◽  
Resource Sharing ◽  
Ad Hoc ◽  
Multicast Routing ◽  
Delivery Ratio ◽  
Grid Environment ◽  
On Demand ◽  
Reactive Routing ◽  
Grid Topology ◽  
Mathematical Problems

Grid computing came into existence as a manner of sharing heavy computational loads among multiple computers to be able to compute highly complex mathematical problems. The grid topology is highly flexible and easily scalable, allowing users to join and leave the grid without the hassle of time and resource-hungry identification procedures, having to adjust their devices or install additional software. The goal of grid computing is described as “to provide flexible, secure and coordinated resource sharing among dynamic collections of individuals, institutions and resources”. AODV is an on-demand (reactive) algorithm capable of both unicast and multicast routing. In this paper, AODV has been modified by varying some of the configuration parameters used in this algorithm to improve its performance. This modified protocol i.e. A-AODV (advanced ad hoc on demand distance vector) has been compared with AODV in grid environment. The simulations have shown that A-AODV is able to achieve high throughput and packet delivery ratio and average end-to-end delay is reduced.

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