The use of electronic B2B ordering systems by customers in continental AG company

The main goal of this paper is to introduce e-Business characteristics and companies' approach to its adoption. The basic difference between e-Commerce and e-Business is defined too. E-Business usage and its adoption are mentioned in first part of this paper. The Internet and information and communication technology (ICT) evolution are important factors in e-Business. Large companies use e-Business because of costs reduction and more effective systems of ordering and selling. E-Business adoption is not very useful and profitable for small and middle sized companies. The second part of this paper is about practical e-Business implementation in Continental AG Company. The unique e-Business system for automotive industry is presented. This company is one of the market leaders in tyres and automotive systems producers worldwide. The case study deals with the analysis of electronic commerce systems within the company Continental AG. The company carries out electronic business transactions in the form of traditional EDI and adhoc EDI. The practical example shows CRM implementation through e-Business in the specific company. Building and enhancing CRM through e-Business is clearly demonstrated on personalization of adhoc EDI system in Continental AG. The research results about B2B purchasing systems satisfaction are presented

Interference-Aware Fair Rate Control in Wireless Sensor Networks

In a wireless sensor network of N nodes transmitting data to a single base station, possibly over multiple hops, what distributed mechanisms should be implemented in order to dynamically allocate fair and efficient transmission rates to each node? Our interferenceaware fair rate control (IFRC) detects incipient congestion at a node by monitoring the average queue length, communicates congestion state to exactly the set of potential interferers using a novel low-overhead congestion sharing mechanism, and converges to a fair and efficient rate using an AIMD control law. We evaluate IFRC extensively on a 40-node wireless sensor network testbed. IFRC achieves a fair and efficient rate allocation that is within 20-40 % of the optimal fair rate allocation on some network topologies. Its rate adaptation mechanism is highly effective: we did not observe a single instance of queue overflow in our many experiments. Finally, IFRC can be extended easily to support situations where only a subset of the nodes transmit, where the network has multiple base stations, or where nodes are assigned different transmission weights