Distributed Resource Allocation in Ad Hoc Network Clusters
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Solution Overview
Problem
Existing methods for allocating time-frequency resources in radio networks, particularly in multi-hop Ad Hoc networks, face challenges in efficiently managing resources without a central station, leading to sub-optimal usage and conflicts, especially in dynamic and large-scale networks.
Innovation Solution
A distributed method for dynamically allocating time-frequency resources among groups of stations using a constraint graph and arbitration function to resolve conflicts, allowing for decentralized, efficient, and conflict-free allocation of resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a central station manages resource allocations, then allocation control and conflict resolution are centralized, but responsiveness and robustness deteriorate in large-scale multi-hop networks
Solution Approach 1:
The patent segments the network into clusters with cluster heads that perform localized resource allocation. Each cluster head manages allocations within its cluster independently, while clusters coordinate through a constraint graph. This segmentation eliminates the single-point bottleneck of central station management while maintaining organized control, thereby improving responsiveness and robustness in large-scale networks.
Solution Approach 2:
The patent introduces cluster heads as intermediary entities between individual stations and the broader network. These cluster heads collect allocation requests, perform local arbitration, and coordinate with other clusters through signaling exchanges. This intermediary layer distributes the management burden, improving system responsiveness while maintaining coordinated resource allocation across the entire network.
2Ease of manufacture
If pre-defined allocation is assigned to groups of stations, then deployment simplicity is improved, but resource utilization efficiency deteriorates due to inability to adapt to dynamic needs
Solution Approach 1:
The patent implements dynamic resource allocation where clusters can request and receive additional resources based on their current traffic needs and network conditions. The allocation tables are updated through iterative signaling exchanges, allowing the system to adapt to changing demands while maintaining the organized structure of pre-defined clusters. This dynamic adjustment significantly improves resource utilization efficiency compared to static pre-allocation.
Solution Approach 2:
The patent allows allocation parameters such as time slots and frequencies to be dynamically adjusted based on network conditions and cluster requirements. The constraint graph and arbitration function enable parameters to be modified in response to changing traffic patterns, ensuring optimal resource utilization while maintaining systematic control through the cluster structure.
3Adaptability or versatility
If decentralized allocation is implemented, then responsiveness and adaptability are improved, but allocation stability and conflict resolution capability worsen
Solution Approach 1:
The patent establishes pre-defined cluster structures and constraint graphs before resource allocation begins. These preliminary structures provide a stable framework that guides decentralized allocation decisions. By pre-organizing the network into clusters with defined relationships, the system maintains stability while allowing flexible, responsive allocation within the established framework through the arbitration function.
Solution Approach 2:
The patent implements feedback mechanisms where clusters exchange signaling information about their allocation status and needs. The arbitration function uses this feedback to make stable, coordinated decisions across clusters. This feedback loop ensures that decentralized allocation decisions are informed by current network state, maintaining both responsiveness to local conditions and overall allocation stability through coordinated adjustments.
4Productivity
If arbitration function is used to resolve conflicts between clusters, then resource allocation efficiency is improved, but signaling overhead and complexity increase
Solution Approach 1:
The patent segments the arbitration process into cluster-level operations rather than requiring network-wide centralized arbitration. Each cluster head performs local arbitration within its cluster using the constraint graph, reducing the scope and complexity of signaling required. This segmented approach maintains high resource allocation efficiency while minimizing signaling overhead compared to global arbitration mechanisms.
Data Source
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AI summary
The invention concerns a distributed method for dynamically allocating time and frequency resources in a network comprising multiple stations, the stations being organized into clusters (or interface) of multiple stations, each cluster including an allocation table Tsi, each unit exchanging via a signalling protocol said allocation table with the other clusters which are defined as being in conflict with it by a constraint graph, the method using an arbitrating function to settle conflicts and attributions of allocations among the conflicting clusters based on the constraint graph. The invention is characterized in that it includes at least the following steps: each interface transmits to the interfaces K indicated as being conflicting in the constraint graph, the table of allocations which is associated with it; an interface Ji watches for each allocation AJi which it has written in its table TJi whether the allocation AJi is used in the table received from an interface K which is conflicting; the interface Ji uses the arbitrating function to modify the allocation AJi in the table TJi.