Mobile devices with 3G/4G networking often waste energy in the so-called “tail time” during which the radio is kept on even though no communication is occurring. Prior work has proposed policies to reduce this energy waste by batching network requests. However, this work is challenging to apply in practice due to a lack of mechanisms. In response, we have developed DelayD roid, a framework that allows a developer to add the needed policy to existing, unmodified Android applications(apps) with no human effort as well as no SDK/OS changes. This allows such prior work(as well as our own policies) to be readily deployed and evaluated. The DelayD roid compile-time uses static analysis and bytecode refactoring to identify method calls that send network requests and modify such calls to detour them to the DelayD roid run-time. The run-time then applies a policy to batch them, avoiding the tail time energy waste. DelayD roid also includes a cross-app communication mechanism that supports policies that optimize across multiple apps running together, and we propose a policy that does so. We evaluated the correctness and universality of the DelayD roid mechanisms on14 popular Android apps chosen from the Google App Store. To evaluate our proposed policy, we studied three DelayD roid-enabled apps(weather forecasting, email client, and news client) running together, finding that the DelayD roid mechanisms combined with our policy can reduce 3G/4G tail time energy waste by 36%. Mobile devices with 3G / 4G networking often waste energy in the so-called “tail time” during which the radio is kept on even though no communication is occurring. Prior work has proposed policies to reduce this energy waste by batching network requests. However, this work is challenging to apply in practice due to a lack of mechanisms. In response, we have developed DelayD roid, a framework that allows a developer to add the needed policy to existing, unmodified Android applications (apps) with no human effort This well as no work SDK (as well as our own policies) to be deployed and as evaluated. The DelayD roid compile-time uses static and bytecode refactoring to identify method calls that send network requests and modify such calls to detour them to the DelayD roid run-time. The run-time then applies a policy to batch them, avoiding the tail time energy waste. DelayD roid also includes a cross-app communication mechanism that supports pol icies that optimize across multiple apps running together, and we propose a policy that does so.. We evaluated the correctness and universality of the DelayD roid mechanisms on14 popular Android apps chosen from the Google App Store. To evaluate our proposed policy, we studied three DelayD roid-enabled apps (weather forecasting, email client, and news client) running together, finding that the DelayD roid machines combined with our policy can reduce 3G / 4G tail time energy waste by 36%.