<?xml version="1.0" encoding="UTF-8"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-10-23T16:04:34Z</responseDate><request verb="GetRecord" identifier="oai:gumushane-rdlopen.rawdatalibrary.net:gumushane/13770" metadataPrefix="oai_dc">https://gumushane-rdlopen.rawdatalibrary.net/oai/request</request><GetRecord><record><header><identifier>oai:gumushane-rdlopen.rawdatalibrary.net:gumushane/13770</identifier><datestamp>2026-10-22T10:21:45Z</datestamp><setSpec>openaire</setSpec><setSpec>com_gumushane_10000</setSpec><setSpec>col_gumushane_10001</setSpec><setSpec>com_gumushane_10007</setSpec><setSpec>col_gumushane_10171</setSpec></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:title>TREE TOPOLOGY-BASED RESOURCE ALLOCATION AND DISCOVERY ALGORITHM FOR ONE HOP</dc:title><dc:creator>Genemo, Musa Dima</dc:creator><dc:creator>Saroja, Yalamanchili</dc:creator><dc:creator>Gopi, Kistam</dc:creator><dc:creator>Mutyam, Veeramani</dc:creator><dc:creator>Reddy, Bhargavi Peddi</dc:creator><dc:creator>Navatejareddy, Ramireddy</dc:creator><dc:creator>Madala, Srinivasa Rao</dc:creator><dc:creator>Sai, Nimmagadda Yaswanth</dc:creator><dc:creator>Koteswararao, K.</dc:creator><dc:subject>Caching</dc:subject><dc:subject>Deficient</dc:subject><dc:subject>Donor</dc:subject><dc:subject>Optimal</dc:subject><dc:subject>Resource Allocation</dc:subject><dc:subject>Topology</dc:subject><dc:description>The components of a distributed system include multiple computing nodes which may use different types of hardware and connect to each other through a communication network that operates without shared memory or clock systems. The primary advantage of distributed systems enables organizations to share resources which results in faster computing times together with increased data availability and system reliability. The process of resource sharing requires organizations to first identify their resources and then assign those resources before anyone can access them. Computer systems implement caching to store frequently used data and program segments. The new caching technique called virtual caching enables a host node to delegate its cache authority for specific pages to nearby nodes who can use its partial cache space. The virtual caching protocol specifies neither the client node's process for accessing virtual cache nor its method for retrieving virtual cache from distant servers. The resource discovery and allocation problem needs us to develop a solution for this particular issue. The resource donation process requires us to find donor nodes who have extra resources while we need to assess which resources will be given to deficient nodes at each connected network point. Our goal is to achieve complete fulfillment of requests which deficient nodes make for resources. The importance of virtual caching lies in the fact that it doesn't require physical movements of cache. The requirements of the system determine when virtual cache allocation can be modified. The proposed heuristics provide efficient performance because they require minimal time and perform limited communication operations. We assess distribution quality through a comparison between heuristic distribution results and the distribution outcomes from the ILP problem solution. We present and assess several heuristics which aim to reduce unfulfilled resource requests that arise from resource-deficient nodes during their resource search process which has a maximum distance of two hops. The paper restricts its analysis to single hop operations only. The paper demonstrates through its research that this algorithm reaches optimal solution status based on our established benchmark criteria. The resource distribution for bounded hops restricts its operations to one-hop resource distribution. Every resource-surplus node transfers additional nodes to other nodes while maintaining its own resource balance without reaching resource-deficient status. Load distribution cannot be divided into infinite parts. Our research focuses on measuring the fulfillment level for each resource-deficient node request.</dc:description><dc:publisher>Little Lion Scientific</dc:publisher><dc:date>2026</dc:date><dc:type>Article</dc:type><dc:identifier>https://rdlopen.rawdatalibrary.net/r/gumushane/13770</dc:identifier><dc:identifier>https://doi.org/10.5281/zenodo.20252257</dc:identifier><dc:identifier>1992-8645</dc:identifier><dc:language>en</dc:language><dc:relation>Journal of Theoretical and Applied Information Technology</dc:relation><dc:rights>info:eu-repo/semantics/closedAccess</dc:rights><dc:type>info:eu-repo/semantics/article</dc:type><dc:identifier>https://gumushane-rdlopen.rawdatalibrary.net/tr/items/gumushane/13770</dc:identifier></oai_dc:dc></metadata></record></GetRecord></OAI-PMH>