arXiv subjects

Jonathan Ponniah

Publications and source records attributed to Jonathan Ponniah.

5 recordsLinked to original sources

arXiv2022

Compress-Forward Schemes for General Networks

Compress-forward (CF) schemes are studied in general networks. The CF rate for the one-relay channel defines outerbounds on both the CF rate for general networks and the compression rate-vector region supporting this rate. We show the outerbound is achievable using regular decoding with constant encoding delays, avoiding the exponential delays and restrictions on bidirectional communication in noisy network coding and backward decoding. The concept of layering is introduced to harmonize regular CF schemes with the framework of flow decomposition in the decode-forward setting. Layerings correspond to regular decoding schemes. Any desired compression rate-vector in the outerbound is achievable by some layering, which is found using the same "shift" operation in flow decomposition. In separate work, we show that "shifting" minimizes the operations needed to find layerings and thus minimizes the complexity of the compression rate-vector region.

cs.IT↗

arXiv2021

Multi-Agent Belief Sharing through Autonomous Hierarchical Multi-Level Clustering

Coordination in multi-agent systems is challenging for agile robots such as unmanned aerial vehicles (UAVs), where relative agent positions frequently change due to unconstrained movement. The problem is exacerbated through the individual take-off and landing of agents for battery recharging leading to a varying number of active agents throughout the whole mission. This work proposes autonomous hierarchical multi-level clustering (MLC), which forms a clustering hierarchy utilizing decentralized methods. Through periodic cluster maintenance executed by cluster-heads, stable multi-level clustering is achieved. The resulting hierarchy is used as a backbone to solve the communication problem for locally-interactive applications such as UAV tracking problems. Using observation aggregation, compression, and dissemination, agents share local observations throughout the hierarchy, giving every agent a total system belief with spatially dependent resolution and freshness. Extensive simulations show that MLC yields a stable cluster hierarchy under different motion patterns and that the proposed belief sharing is highly applicable in wildfire front monitoring scenarios.

cs.RO↗

arXiv2018

Flow Decomposition

The decode-forward achievable region is studied for general networks. The region is subject to a fundamental tension in which nodes individually benefit at the expense of others. The complexity of the region depends on all the ways of resolving this tension. Two sets of constraints define an outer-bound on the decode-forward region: first, the conventional mutual-information inequalities implied by the one-relay channel, and second, causality constraints that ensure nodes only forward messages they have already decoded. The framework of flow decomposition is introduced to show these constraints are also sufficient. Flow decomposition provides a way of manipulating regular decode-forward schemes without the long encoding delays and restrictions on bidirectional communication of backward decoding. The two structures that define a flow decomposition are flows and layerings. Flows specify the nodes which encode messages from each source (i.e., the routes) and the encoding delays. Layerings specify the messages decoded at a specific node in the channel. We focus on two types of flow: hierarchical flow, with tree-like routes, and all-cast flow, where each route covers all nodes. For arbitrary flows of either type and any rate-vector satisfying the mutual-information constraints at a specific node, we prove there are equivalent flows and a layering that satisfy both the mutual-information and causality constraints. In separate work, we show that only the mutual-information constraints are active in channels with hierarchical flow, which implies the achievable region has minimal complexity. In channels with all-cast flow, the achievable region is computable.

cs.IT↗

arXiv2016

An Achievable Rate Region for the Two-Way Multiple-Relay Channel

We propose an achievable rate-region for the two-way multiple-relay channel using decode-and-forward block Markovian coding. We identify a conflict between the information flow in both directions. This conflict leads to an intractable number of decode-forward schemes and achievable rate regions, none of which are universally better than the others. We introduce a new concept in decode-forward coding called ranking, and discover that there is an underlying structure to all of these rate regions expressed in the rank assignment. Through this discovery, we characterize the complete achievable rate region that includes all of the rate regions corresponding to the particular decode-forward schemes. This rate region is an extension of existing results for the two-way one-relay channel and the two-way two-relay channel.

cs.IT↗

arXiv2013

A System-Theoretic Clean Slate Approach to Provably Secure Ad Hoc Wireless Networking

Traditionally, wireless network protocols have been designed for performance. Subsequently, as attacks have been identified, patches have been developed. This has resulted in an "arms race" development process of discovering vulnerabilities and then patching them. The fundamental difficulty with this approach is that other vulnerabilities may still exist. No provable security or performance guarantees can ever be provided. We develop a system-theoretic approach to security that provides a complete protocol suite with provable guarantees, as well as proof of min-max optimality with respect to any given utility function of source-destination rates. Our approach is based on a model capturing the essential features of an adhoc wireless network that has been infiltrated with hostile nodes. We consider any collection of nodes, some good and some bad, possessing specified capabilities vis-a-vis cryptography, wireless communication and clocks. The good nodes do not know the bad nodes. The bad nodes can collaborate perfectly, and are capable of any disruptive acts ranging from simply jamming to non-cooperation with the protocols in any manner they please. The protocol suite caters to the complete life-cycle, all the way from birth of nodes, through all phases of ad hoc network formation, leading to an optimized network carrying data reliably. It provably achieves the min-max of the utility function, where the max is over all protocol suites published and followed by the good nodes, while the min is over all Byzantine behaviors of the bad nodes. Under the protocol suite, the bad nodes do not benefit from any actions other than jamming or cooperating. This approach supersedes much previous work that deals with several types of attacks.

cs.NI↗