Abstract-This article provides an overview of the multimedia broadcast/multicast service (MBMS) for universal mobile telecommunications system (UMTS) networks. We first outline the features of UMTS networks as defined by the 3rd generation partnership project (3GPP) in order to provide a background for the discussion to follow. We then present the overall MBMS architecture, the services that it provides to the users and the differences between the broadcast and multicast options. The implementation details of MBMS are explained in terms of the modifications needed to the network, the new signaling procedures required and the impact of MBMS on the radio part of the network. We then describe how the security architecture of UMTS is used to support content protection and key distribution for MBMS groups. We evaluate the prospects of MBMS by comparing it first with IP multicast and then with DVB-H, considered by many to be the closest competitor of MBMS. Finally, we conclude with a discussion of the technical and business challenges still faced by MBMS.
Peak demand is a major challenge for power utilities across the world. Demand Response (DR) is considered to be effective in addressing peak demand by altering consumption of end consumers, so as to match supply capability. However, an efficient DR system needs to respect end consumer convenience and understand their propensity of participating in a particular DR event, while altering the consumer demand. Understanding such preferences is non-trivial due to the large-scale and variability of consumers and the infrastructure changes required for collecting essential (smart meter and/or appliance specific) data.In this paper, we propose an inclusive DR system, iDR, that helps an electricity provider to design an effective demand response event by analyzing its consumers' houselevel consumption (smart meter) data and external context (weather conditions, seasonality etc.) data. iDR combines analytics and optimization to determine optimal power consumption schedules that satisfy an electricity provider's DR objectives -such as reduction in peak load -while minimizing the inconvenience caused to consumers associated with alteration in their consumption patterns. iDR uses a novel context-specific approach for determining end consumer baseline consumptions and user convenience models. Using these consumer specific models and past DR experience, iDR optimization engine identifies -(i) when to execute a DR event, (ii) who are the consumers to be targeted for the DR, and (iii) what signals to be sent. Some of iDR's capabilities are demonstrated using real-world house-level as well as appliance-level data.
Demand response (DR) has received significant attention in recent years and several DR programs are being deployed and evaluated worldwide. DR systems provide a wide range of economic and operational benefits to different stakeholders of the electrical power system including consumers, generators and distributors. DR can be achieved through a number of different mechanisms such as direct-load-control, incentives, pricing signals, or a combination of these schemes. Due to the remarkable variation in demand response systems, it becomes a challenge to evaluate and compare the effectiveness of different DR programs holistically. In this work, we define a number of different performance metrics that could be used to evaluate DR programs based on peak reduction, demand variation and reshaping, and economic benefits.
Abstract. Grid technology offers numerous opportunities for the players involved. Despite the fact that the academic community has already exploited many of them, there is an evident reluctance from the business community to act likewise. Recent analysis reveals that the problem lies in overcoming certain business barriers rather than technological ones. At this stage understanding the real-life economic issues from a business perspective is deemed as more important than gaining understanding of complex theoretical economical problems, such as those related to accounting or resource sharing mechanisms especially in cases where the players do not exhibit the required technological expertise. This paper is stimulated from interaction with players from the industry and aims to fill this gap. In particular, we identify and evaluate a number of economic issues that should be taken into consideration by industrial players so that their trust and confidence in the adoption of this promising technology be increased. 1
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