Mobile Edge Computing Offloading for Energy-Constrained Devices
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Solution Overview
Problem
The increasing complexity of communication systems leads to higher computational demands on mobile devices, which exceed the capabilities of current battery technology, resulting in energy consumption challenges and reduced user experience due to limited computational resources.
Innovation Solution
Mobile Edge Computing (MEC) technology offloads computationally intensive tasks from user equipment to edge hosts, allowing for the execution of applications closer to cellular network subscribers, reducing network congestion and enhancing performance by leveraging multiple radio access technologies and network function virtualization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If computational tasks are performed by mobile devices to meet increasing application complexity, then application performance is improved, but energy consumption increases beyond battery capabilities
Solution Approach 1:
The patent extracts computationally intensive application functions from mobile devices and relocates them to edge hosts. The mobile device retains only lightweight client applications that communicate with remote servers, while heavy processing tasks are performed remotely at the network edge, thereby reducing local energy consumption while maintaining computational capability.
Solution Approach 2:
The patent introduces edge hosts as intermediary computing resources between mobile devices and remote cloud servers. These edge hosts provide computational services to mobile devices without requiring the devices themselves to perform heavy computations, thus mediating between limited device resources and high-performance computing needs.
2Adaptability or versatility
If application complexity increases to meet evolving communication systems, then functionality is improved, but computational requirements exceed mobile device capabilities
Solution Approach 1:
The patent extracts complex application logic and processing functions from mobile devices and places them on remote edge hosts. Mobile devices run simplified client applications that interact with edge hosts via standardized interfaces, allowing high application complexity to be achieved without increasing device computational resources.
Solution Approach 2:
The patent creates universal edge host platforms that can execute multiple different complex applications and serve multiple mobile devices. These edge hosts provide multi-functional computational services, allowing a single device to access diverse complex applications without having the computational resources to run them locally.
3Use of energy by moving object
If computation is offloaded to edge hosts, then energy consumption is reduced, but network dependency increases
Solution Approach 1:
The patent implements preliminary actions by pre-establishing communication protocols and data formats between mobile devices and edge hosts. Client applications are designed with built-in knowledge of expected server responses and data structures, enabling efficient communication and reducing the need for complex error handling and retries, thus mitigating network dependency risks.
Data Source
AI summary
Systems, apparatuses, methods, and computer-readable media, are provided for offloading computationally intensive tasks from one computer device to another computer device taking into account, inter alia, energy consumption and latency budgets for both computation and communication. Embodiments may also exploit multiple radio access technologies (RATs) in order to find opportunities to offload computational tasks by taking into account, for example, network/RAT functionalities, processing, offloading coding/encoding mechanisms, and/or differentiating traffic between different RATs. Other embodiments may be described and/or claimed.