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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 broadcasting. Towards this goal, several broadcast scheduling policies have been proposed. These existing schemes 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 dissertation, we propose SAAB, 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 characteristics 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 broadcast scheduling policies.

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 broadcasting. Towards this goal, several broadcast scheduling policies have been proposed. These existing schemes 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 dissertation, we propose SAAB, 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 characteristics 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 broadcast scheduling policies.