Since the release of the first smart phone from Apple in the year 2007, smart phones in general experience a fast growth of rising popularity. A smart phone typically possesses among others a touchscreen display as user interface, a mobile communication for accessing the Internet, and a System-on-a-Chip as an integrated circuit of required components like a central processing unit. This pervasive computing platform derives its required power from a battery, where an end user runs upon it different kinds of applications like a calendar application or a high-end mobile game. Differing in the usage of the local resources from a battery-operated smart phone, a heavy utilization of local resources like playing a resource-demanding application drains the limited resource of energy in few hours. Despite the constant increase of memory, communication, or processing capabilities of a smart phone since the release in 2007, applications are also getting more and more sophisticated and demanding. As a result, the energy consumed on a smart phone was, still is, and will be its main limiting factor.

To prevent the limited resource of energy from a quick exhaustion, researchers propose code offloading for (resource-constrained) mobile devices like smart phones. Code offloading strives for increasing the energy efficiency and execution speed of applications by utilizing a server instance in the infrastructure. To this end, a code offloading approach executes dynamically resource-intensive parts from an application on powerful remote servers in the infrastructure on behalf of a (resource-constrained) mobile device. During the remote execution of a resource-intensive application part on a remote server, a mobile device only waits in idle mode until it receives the result of the application part executed remotely. Instead of executing an application part on its local resources, a (resource-constrained) mobile device benefits from the more powerful resources of a remote server by sending the information required for a remote execution, waiting in idle mode, and receiving the result of the remote execution.

The process of offloading code from a (resource-constrained) mobile device to a powerful remote server in the infrastructure, however, faces different problems. For instance, code offloading introduces some overhead for additional computation and communication on a mobile device. Moreover, spontaneous disconnections during a remote execution can cause a higher energy consumption and execution time than a local execution on a mobile device without code offloading. To this end, this dissertation addresses the whole process of offloading code from a mobile device not only to one but also to multiple remote resources, comprising the following steps:

1) First, code offloading has to identify feasible parts from an application for a remote execution, where the distributed execution of the identified application part is more beneficial than its local execution. A feasible part for a remote execution typically has the following properties: A low size of information required for transmission before a remote execution, a resource-intensive computation not accessing local sensors, and a low size of information required for transmission after a remote execution. In the area of identification of application parts for a remote execution, this dissertation presents an approach based on code annotations from application developers that automatically transforms a monolithic execution on a mobile device to a distributed execution on multiple heterogeneous resources. In contrast to related approaches in the literature, the annotation-based approach requires least interventions from application developers and end users, keeping the overhead introduced on a mobile device low.

2) For an application part identified for a remote execution, code offloading has to determine its execution side, executing the application part either on the local resources of a mobile device or on the remote resource at the infrastructure. In the area of determining the execution side for an application part, this dissertation presents the offloading problem, where a mobile device decides whether to execute an application part locally or remotely. Furthermore, this dissertation also presents an approach called “code bubbling” that shifts the decision making into the infrastructure. In contrast to related approaches in the literature, the decision-based approach on a mobile device and the bubbling-based approach minimize the execution time, energy consumption, and monetary cost for an application.

3) To determine the execution side for an application part identified for a remote execution, code offloading has to obtain different parameters from the application, participating resources, and utilized links. In the area of obtaining the information required from an application, this dissertation presents a bit-flipping approach that dynamically flips a bit at the modification of application-related information. Furthermore, this dissertation also presents an offload-aware Application Programming Interface (API) that encapsulates the application-related information required for code offloading. In contrast to related approaches in the literature, the bit-flipping approach and the offload-aware API provide an efficient gathering of information at run-time, keeping the overhead introduced on a mobile device low.

4) Beside the information from an application, code offloading has to obtain further information from participating resources and utilized links. In the area of obtaining the information required from participating resources and utilized links, this dissertation presents the approach of code bubbling, already mentioned above. In contrast to related approaches in the literature, the bubbling-based approach makes the offload decision at the place where the related information occurs, keeping the overhead introduced on a mobile device, participating resources, and utilized links low.

5) In case of a remote execution of an application part, code offloading has to send the information required for a remote execution to the remote resource that subsequently executes the application part on behalf of the mobile device. In the area of sending the required information and executing an application part remotely, this dissertation presents code offloading with a cache on the remote side. The cache on the remote side serves as a collective storage of results for already executed application parts, avoiding a repeated execution of previously run application parts. In contrast to related approaches in the literature, the caching-aware approach increases the efficiency of code offloading, keeping the energy consumption, execution time, and monetary cost low.

6) While a remote resource executes an application part, code offloading has to handle the occurrence of failures like a failure of the remote resource or a disconnection. In the area of handling the occurrence of failures, this dissertation presents a preemptable offloading of code with safe-points. The preemptable offloading of code with safe-points enables an interruption of an offloading process and a corresponding continuation of a remote execution on a mobile device, without abandoning the complete result calculated remotely so far. Based on a preemptable offloading of code with safe-points, this dissertation further presents a predictive offloading of code with safe-points that minimizes the overhead introduced by safe-point’ing and maximizes the efficiency of a deadline-aware offloading. In contrast to related approaches in the literature, the preemptable approach with safe-point’ing increases the robustness of code offloading in case of failures. Furthermore, the predictive approach for safe-point’ing ensures a minimal responsiveness and a maximal efficiency of applications despite failures.

7) At the end of a remote execution of an application part, code offloading has to gather on the remote resource the required information after the execution and send this information to the mobile device. In the area of gathering the required information, a remote resource utilizes the same approaches as a mobile device, already mentioned above (cf. the bit-flipping approach and the offload-aware API).

8) Last, code offloading has to receive on the mobile device the information from a remote resource, install the information on the mobile device, and continue the execution of the application on the mobile device. In the area of installing the information and continuing the execution locally, a mobile device utilizes the approaches already mentioned above (cf. the bit-flipping approach and the offload-aware API).