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Smartphones are starting to find use in mission-critical applications, such as search-and-rescue operations, wherein the mission capabilities are realized by deploying a collaborating set of services across a group of smartphones involved in the mission. Since these missions are deployed in environments where replenishing resources, such as smartphone batteries, is hard, it is necessary to maximize the lifespan of the mission while also maintaining its real-time Quality of Service (QoS) requirements. To address these requirements, this paper presents a deployment framework called Smart-Deploy, which integrates bin packing heuristics with evolutionary algorithms to produce near-optimal deployment solutions that are computationally inexpensive to compute for maximizing the lifespan of smartphone-based mission critical applications.
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