SLA-Aware Adaptive On-Demand Data Broadcasting in Wireless Environments Adrian Daniel Popescu Mohamed A. Sharaf Cristiana Amza Department of Electrical and Computer Engineering University of Toronto {adrian, msharaf, amza}@eecg.toronto.edu Abstract—In mobile and wireless networks, data broadcasting for popular data items enables the efficient utilization of the limited wireless bandwidth. However, efficient data scheduling schemes are needed to fully exploit the benefits of data broadcast- ing. This motivated the proposal of several broadcast scheduling policies, which have mostly focused on either minimizing response time, or drop rate when requests are associated with hard deadlines. The inherent inaccuracy of hard deadlines in a dynamic mobile environment motivated us to use Service Level Agreements (SLAs) where a user specifies the utility of data as a function of its arrival time. Moreover, SLAs provide the mobile user with an already familiar quality of service specification from wired environments. Hence, in this paper, we propose SAAB which is an SLA-aware adaptive data broadcast scheduling policy for maximizing the system utility under SLA-based performance measures. To achieve this goal, SAAB considers both the char- acteristics of disseminated data objects as well as the SLAs associated with them. Additionally, SAAB automatically adjusts to the system workload conditions which enables it to constantly outperform existing on-demand broadcast scheduling policies. I. I NTRODUCTION With the continuous dependence on wireless data access, it is only natural that mobile users would expect the same Service Level Agreements (SLAs) currently provided to counterpart applications running on their stationary platforms in a wired environment. SLAs provide users with the flexibility to define the utility of delayed data. It also provides a concrete measure for system performance based on the users’ perceived overall utility [14]. In this paper, we argue that SLA is a natural fit for the timely demands of mobile applications accessing time- critical data, including traffic and weather conditions, news headlines, stock quotes, and RSS feeds. Providing SLAs to such applications, together with mechanisms to enforce those SLAs, ensures the usability of mobile applications since they would provide end users with useful information within their pre-specified tolerated delays. Enforcing SLAs requires re-thinking the design of current data dissemination techniques used in wireless networks, es- pecially data broadcasting. Examples of data broadcasting systems include the Multimedia Broadcast Multicast Services (MBMS) [18] and the Terestrial digital broadcasting (ISDB-T) [17]. Towards exploiting these broadcasting capabilities, sev- eral data broadcasting schemes have been developed to reduce the delays in wireless data retrieval [1], [3], [4], [5]. These schemes could be broadly classified into push-based [1] and on-demand (i.e., pull-based) [3], [4], [5], where on-demand data broadcasting has been shown to be more scalable [6]. In particular, under on-demand data broadcasting users submit requests for data items of interest and the broadcast server aggregates requests for the same data item and broadcasts it only once. If a data item is highly popular, then broadcasting that data item to all interested users substantially reduces the number of transmissions. Hence, broadcasting allows for a more efficient utilization of the limited wireless bandwidth, resulting in shorter delays. In order to fully reap the benefits of on-demand data broadcasting, an efficient request scheduler is needed so that to decide the best dissemination order of requested data with the goal of optimizing a certain performance metric. In this paper, we propose such a scheduler for optimizing performance under SLA. This is particularly important in mobile environments where data is accessed under certain time constraints. Exam- ples of such constraints include the battery lifetime of the mobile device [8]. It also includes the spatiotemporal nature of the accessed data as in Location-based services where data is valid only within a local area [22]. Additionally, the SLA requirement is often imposed by the data provider itself so that to maintain a certain performance target. Previous work on data broadcasting has focused mainly on optimizing the user perceived response time incurred in data retrieval [3], [4], [5], [19]. However, optimizing response time is not sufficient to maximize data usability since it overlooks the user’s requirements and expectations. For instance, a user posing a request for available restaurants off an upcoming highway exit would have more stringent timely requirements than a user posing a request for the evening movie schedules. As an alternative to response time, recent research on wire- less data broadcasting has also looked at optimizing drop rate (also known as miss rate) [22], [8], [15]. Under such measure, each request is assigned a hard deadline and the system strives to minimize the number of requests missing their deadlines. However, one drawback of this approach is the complexity and inaccuracy entailed in setting those hard deadlines. Another problem with that approach is that it assumes data to be useless past the pre-specified hard deadline, hence it drops those requests which are prone to missing their deadlines. With response time and drop rate being two extremes on the performance spectrum, SLAs have been used to successfully capture the users’ performance expectations. Moreover, in a mobile environment, SLAs are inherently based on soft dead- 2009 Tenth International Conference on Mobile Data Management: Systems, Services and Middleware 978-0-7695-3650-7/09 $25.00 © 2009 IEEE DOI 10.1109/MDM.2009.25 142 2009 Tenth International Conference on Mobile Data Management: Systems, Services and Middleware 978-0-7695-3650-7/09 $25.00 © 2009 IEEE DOI 10.1109/MDM.2009.25 142