Implementation of fast and effective dynamic pricing schemes in smart grids

Author(s):  
A. Ferreira ◽  
C. Dortolina
Author(s):  
Hailing Zhu ◽  
Andre Nel ◽  
Hendrik Ferreira

Dynamic Spectrum Allocation (DSA) has been viewed as a promising approach to improving spectrum efficiency. With DSA, Wireless Service Providers (WSPs) that operate in fixed spectrum bands allocated through static allocation can solve their short-term spectrum shortage problems resulting from the bursty nature of wireless traffic. Such DSA mechanisms should be coupled with dynamic pricing schemes to achieve the most efficient allocation. This chapter models the DSA problem where a centralized spectrum broker manages “white space” in the spectrum of TV broadcasters and sells the vacant spectrum bands to multiple WSPs, as a multi-stage non-cooperative dynamic game. Furthermore, an economic framework for DSA is presented and a centralized spectrum allocation mechanism is proposed. The simulation results show that the centralized spectrum allocation mechanism with dynamic pricing achieves a DSA implementation that is responsive to market conditions as well as enabling efficient utilization of the available spectrum.


Author(s):  
Ioanna D. Constantiou ◽  
Jörn Altmann

The market of Internet service providers (ISPs) is highly competitive. Although many different pricing schemes could be deployed in this market, two types are mainly offered: flat rate pricing and per-minute pricing. These pricing schemes are criticised for limiting ISPs’ revenues and for not addressing customer’s requirements on service quality. We focus on the ISPs’ business relationships and on their pricing strategies in order to analyse revenue sharing mechanisms. We argue that the introduction of incentive pricing schemes, such as dynamic pricing, may enable provision of service quality by improving revenue sharing among ISPs.


Author(s):  
El-Bahlul Fgee ◽  
Shyamala Sivakumar ◽  
William J. Phillips ◽  
William Robertson

Network multimedia applications constitute a large part of Internet traffic and guaranteed delivery of such traffic is a challenge because of their sensitivity to delay, packet loss and higher bandwidth requirement. The need for guaranteed traffic delivery is exacerbated by the increasing delay experienced by traffic propagating through more than one QoS domain. Hence, there is a need for a flexible and a scalable QoS manager that handles and manages the needs of traffic flows throughout multiple IPv6 domains. The IPv6 QoS manager, presented in this paper, uses a combination of the packets’ flow ID and the source address (Domain Global Identifier (DGI)), to process and reserve resources inside an IPv6 domain. To ensure inter-domain QoS management, the QoS domain manager should also communicate with other QoS domains’ managers to ensure that traffic flows are guaranteed delivery. In this scheme, the IPv6 QoS manager handles QoS requests by either processing them locally if the intended destination is located locally or forwards the request to the neighboring domain’s QoS manager. End-to-end QoS is achieved with an integrated admission and management unit. The feasibility of the proposed QoS management scheme is illustrated for both intra- and inter-domain QoS management. The scalability of the QoS management scheme for inter-domain scenarios is illustrated with simulations for traffic flows propagating through two and three domains. Excellent average end-to-end delay results have been achieved when traffic flow propagates through more than one domain. Simulations show that packets belonging to non-conformant flows experience increased delay, and such packets are degraded to lower priority if they exceed their negotiated traffic flow rates. Many pricing schemes have been proposed for QoS-enabled networks. However, integrated pricing and admission control has not been studied in detail. A dynamic pricing model is integrated with the IPv6 QoS manager to study the effects of increasing traffic flows rates on the increased cost of delivering high priority traffic flows. The pricing agent assigns prices dynamically for each traffic flow accepted by the domain manager. Combining the pricing strategy with the QoS manager allows only higher priority traffic packets that are willing to pay more to be processed during congestion. This approach is flexible and scalable as end-to-end pricing is decoupled from packet forwarding and resource reservation decisions. Simulations show that additional revenue is generated as prices change dynamically according to the network congestion status.


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