Cooperative IoT Network Resource Sharing Framework
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Solution Overview
Problem
Current solutions for addressing the increased computational and memory demands of IoT edge devices, such as increasing resources or offloading tasks to cloud servers, face challenges like power consumption, cost, hardware replacement, and latency, and often require stable internet connections which may not be available.
Innovation Solution
A system and method enabling cooperative sharing of resources among network devices through a framework that allows devices to broadcast available resources, track them in a network resource ledger, and request access to needed resources based on factors like reliability and proximity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Power
If computational and memory capabilities of edge devices are increased to handle IoT workloads, then processing performance is improved, but power consumption increases and battery life shortens
Solution Approach 1:
Multiple edge devices are merged into a cooperative network where computational resources are shared collectively. Instead of each device independently increasing its own capabilities, the network combines available CPU cycles, memory, and processing power across devices to handle workloads, thereby improving overall processing performance without requiring individual devices to consume more power.
Solution Approach 2:
Edge devices are designed to perform multiple functions by sharing resources across the network. A single device can provide computational power, sensor data, or memory to multiple other devices as needed, making each device universally useful for various tasks rather than requiring specialized high-power hardware for each function.
2Power
If computational and memory capabilities of edge devices are increased, then processing performance is improved, but hardware replacement costs increase and feasibility decreases
Solution Approach 1:
The system merges the computational capabilities of existing edge devices into a shared network resource pool. Rather than replacing individual devices with more powerful hardware, the network combines the available processing power across multiple devices to achieve the required computational capability, making the solution feasible for deployed IoT devices without requiring hardware replacement.
3Power
If tasks are offloaded to cloud servers, then processing capability is improved, but latency increases and connection reliability requirements increase
Solution Approach 1:
The system provides cloud-like computational resources locally at the edge device level. By establishing a cooperative network of edge devices that can share resources peer-to-peer, the solution delivers improved processing capability without requiring connection to remote cloud servers, thereby eliminating the latency and connection reliability issues associated with cloud offloading.
4Power
If cloud servers are added to provide computing capabilities, then processing capability is improved, but system complexity and cost increase
Solution Approach 1:
Edge devices in the cooperative network serve each other by automatically sharing available resources based on local needs. The network manages resource allocation and device coordination autonomously without requiring centralized cloud server infrastructure, thereby reducing system complexity and operational cost while maintaining improved processing capability.
Data Source
AI summary
A system and method for optimizing the performance and capabilities of existing wireless networks by enabling cooperative sharing of resources among the network devices in the IoT network. The network devices may share computational resources, sensors or memory capabilities, among other resources. This cooperating sharing is enabled through the use of a framework. The framework enables devices to broadcast the resources that are available for sharing. These resources can be incorporated into a network resource ledger that tracks all of the sharable resources in the network, and the owner of each respective resource. In this way, network devices that are in need of a resource, such as computational power or a sensor, can request that resource from a neighboring network device.