Informed mobile prefetching

Abstract

Prefetching is a double-edged sword. It can hide the latency of data transfers over poor and intermittently connected wireless networks, but the costs of prefetching in terms of increased energy and cellular data usage are potentially substantial, particularly for data prefetched incorrectly. Weighing the costs and benefits of prefetching is complex, and consequently most mobile applications employ simple but sub-optimal strategies.Rather than leave the job to applications, we argue that the underlying mobile system should provide explicit prefetching support. Our prototype, IMP, presents a simple interface that hides the complexity of the prefetching decision. IMP uses a cost-benefit analysis to decide when to prefetch data. It employs goal-directed adaptation to try to minimize application response time while meeting budgets for battery lifetime and cellular data usage. IMP opportunistically uses available networks while ensuring that prefetches do not degrade network performance for foreground activity. It tracks hit rates for past prefetches and accounts for networkspecific costs in order to dynamically adapt its prefetching strategy to both the network conditions and the accuracy of application prefetch disclosures. Experiments with email and news reader applications show that IMP provides predictable usage of budgeted resources, while lowering application response time compared to the oblivious strategies used by current applications.

Is there a case for mobile phone content pre-staging?

“…The "last mile" of the cellular network is constrained by spectrum that needs to be shared by multiple users. In this scenario, both forward caching [2] and content pre-fetching [3] do not help since an object traverses the last mile at least once for each user requesting it. Hence, caching needs to be reassessed for cellular networks.…”

Optimal Relay Selection and Data Forwarding Strategies for Secure Mobile Health Monitoring Services

“…For instance, [2] proposes a cost-benefit model to decide when to prefetch user data. The objective is to minimize the application response time through prefetching, while meeting budget constraints for battery lifetime and cellular data plan usage.…”

Edge Reduce: Eliminating Mobile Network Traffic Using Application-Specific Edge Proxies

“…A wide range of prior work exists on effective prefetching strategies, e.g. in the context of web applications exploiting spatial locality, pattern mining and contextual information [6], [27]. For simplicity, however, mobile client applications typically do not use sophisticated prefetching policies but prefetch all objects instead.…”

“…While this improves application response time when the user accesses prefetched content, it increases the amount of data transmitted over the RAN. Client applications often employ simple strategies such as prefetching all objects [6], which are wasteful. For example, Twitter clients typically prefetch all user profile images associated with a list of messages, even if only a few images will be viewed by the user.…”