A Service-Oriented Approach for Decomposing and Verifying Hybrid System Models

Author(s):  
Timm Liebrenz ◽  
Paula Herber ◽  
Sabine Glesner
2007 ◽  
Vol 46 (3) ◽  
pp. 549-564 ◽  
Author(s):  
A. J. Keel ◽  
M. A. Orr ◽  
R. R. Hernandez ◽  
E. A Patrocinio ◽  
J. Bouchard

Author(s):  
Maarten W.A. Steen ◽  
Patrick Strating ◽  
Marc M. Lankhorst ◽  
Hugo W.L. ter Doest ◽  
Maria-Eugenia Iacob

Service orientation is a new paradigm, not only for software engineering but also for the broader topic of enterprise architecture. This chapter studies the relevance and impact of the service concept and service orientation to the discipline of enterprise architecture. It provides ideas on how to set up a service-oriented enterprise architecture. It is argued that a service-oriented approach to enterprise architecture provides better handles for architectural alignment and business and IT alignment, in particular.


Author(s):  
Prabhakar Rontala Subramaniam

An attempt in implementing on-demand, QoS supported Vehicular Ad hoc Network (VANET) routing algorithms has taken new dimensions. Delivering information in time to achieve reliability across vehicles (nodes) is still being a challenge among the VANET research groups. An effort to develop a QoS adaptive routing schemes using soft computing techniques is made in this research work. SADVA – An adaptive fuzzy based QoS service oriented approach for VANET is presented in this paper. The performance of SADVA is compared with AODV (Perkins, Royer, & Das, 2003), GV-GRID (Li, & Yu, 2007), DSR (Johnson, Maltz, & Hu, 2004), FSR (Gerla, 2002), DYMO (Chakeres, & Perkins, 2006), REDEM (Prabhakar, Sivanandham, & Arunkumar, 2011b), and QARS (Prabhakar et al, 2011a). SADVA employs fuzzy logic system to determine the vehicle's speed over an effective time period for different types of service in use between multiple VANET nodes to engage or cooperate in communication. This chapter focuses on designing and developing QoS aware routing protocol for multi-hop VANET. Metrics such as number of packets received per second, percentage of packet loss and time for route establishment are used to analyse the network situation. Simulation test runs are carried out using Two Ray Ground propagation model where vehicular traffic is generated according to a Poisson process.


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