Towards Cache-Assisted Hierarchical Detection for Real-Time Health Data Monitoring in IoHT

Real-time health data monitoring is pivotal for bolstering road services’safety,intelligence,and efficiency within the Internet of Health Things(IoHT)framework.Yet,delays in data retrieval can markedly hinder the efficacy of big data awareness detection systems.We advocate for a collaborative caching approach involving edge devices and cloud networks to combat this.This strategy is devised to streamline the data retrieval path,subsequently diminishing network strain.Crafting an adept cache processing scheme poses its own set of challenges,especially given the transient nature of monitoring data and the imperative for swift data transmission,intertwined with resource allocation tactics.This paper unveils a novel mobile healthcare solution that harnesses the power of our collaborative caching approach,facilitating nuanced health monitoring via edge devices.The system capitalizes on cloud computing for intricate health data analytics,especially in pinpointing health anomalies.Given the dynamic locational shifts and possible connection disruptions,we have architected a hierarchical detection system,particularly during crises.This system caches data efficiently and incorporates a detection utility to assess data freshness and potential lag in response times.Furthermore,we introduce the Cache-Assisted Real-Time Detection(CARD)model,crafted to optimize utility.Addressing the inherent complexity of the NP-hard CARD model,we have championed a greedy algorithm as a solution.Simulations reveal that our collaborative caching technique markedly elevates the Cache Hit Ratio(CHR)and data freshness,outshining its contemporaneous benchmark algorithms.The empirical results underscore the strength and efficiency of our innovative IoHT-based health monitoring solution.To encapsulate,this paper tackles the nuances of real-time health data monitoring in the IoHT landscape,presenting a joint edge-cloud caching strategy paired with a hierarchical detection system.Our methodology yields enhanced cache efficiency and data freshness.The corroborative numerical data accentuates the feasibility and relevance of our model,casting a beacon for the future trajectory of real-time health data monitoring systems.

Caching Scheme Based on Power-Law Characteristic in Unstructured P2P Networks

In order to reduce the traffic load and improve the availability of the shared resources in unstructured P2P networks, a caching scheme combining alternative index and adaptive replication （AIAR） is presented. AIAR uses random walk mechanism to disperse the caching information of resources in the network based on its power-law characteristic, and dynamically adjusts replicas according to the visit frequency on resources and the degree information of peers. Subsequent experimental results show that the proposed AIAR scheme is beneficial to improve the search performance of success rate and respond speed. In addition, compared to some existing caching scheme, AIAR can perform much better in success rate, especially in a dynamic environment.

A P2P streaming service architecture with distributed caching

Multimedia streaming served through peer-to-peer (P2P) networks is booming nowadays. However, the end-to-end streaming quality is generally unstable due to the variability of the state of serve-peers. On the other hand, proxy caching is a bandwidth-efficient scheme for streaming over the Internet, whereas it is a substantially expensive method needing dedicated powerful proxy servers. In this paper, we present a P2P cooperative streaming architecture combined with the advantages of both P2P networks and multimedia proxy caching techniques to improve the streaming quality of participating clients. In this frame- work, a client will simultaneously retrieve contents from the server and other peers that have viewed and cached the same title before. In the meantime, the client will also selectively cache the aggregated video content so as to serve still future clients. The associate protocol to facilitate the multi-path streaming and a distributed utility-based partial caching scheme are detailedly dis- cussed. We demonstrate the effectiveness of this proposed architecture through extensive simulation experiments on large, Inter- net-like topologies.

A Hybrid Cache Placement Scheme for Multi-Hop Wireless Service Network

In this paper,a hybrid cache placement scheme for multihop wireless service networks is proposed. In this scheme,hot nodes in data transferring path are mined up by means of rout-ing navigation graph,and whole network is covered with network clustering scheme. A hot node has been chosen for cache place-ment in each cluster,and the nodes within a cluster access cache data with no more than two hops. The cache placement scheme reduces data access latency and workload of the server node. It also reduces the average length of data transferring,which means that fewer nodes are involved. The network system energy con-sumption decreased as involved relay nodes reduced. The per-formance analysis shows that the scheme achieves significant system performance improvement in network environment,with a large number of nodes.

Information Centric Networking Based Cooperative Caching Framework for 5G Communication Systems

The demands on conventional communication networks are increasing rapidly because of the exponential expansion of connected multimedia content.In light of the data-centric aspect of contemporary communication,the information-centric network(ICN)paradigm offers hope for a solution by emphasizing content retrieval by name instead of location.If 5G networks are to meet the expected data demand surge from expanded connectivity and Internet of Things(IoT)devices,then effective caching solutions will be required tomaximize network throughput andminimize the use of resources.Hence,an ICN-based Cooperative Caching(ICN-CoC)technique has been used to select a cache by considering cache position,content attractiveness,and rate prediction.The findings show that utilizing our suggested approach improves caching regarding the Cache Hit Ratio(CHR)of 84.3%,Average Hop Minimization Ratio(AHMR)of 89.5%,and Mean Access Latency(MAL)of 0.4 s.Within a framework,it suggests improved caching strategies to handle the difficulty of effectively controlling data consumption in 5G networks.These improvements aim to make the network run more smoothly by enhancing content delivery,decreasing latency,and relieving congestion.By improving 5G communication systems’capacity tomanage the demands faced by modern data-centric applications,the research ultimately aids in advancement.

In-network caching for energy efficiency in content-centric networking

Recently, Internet energy efficiency is paid more and more attention. New Internet architectures with more energy efficiency were proposed to promote the scalability in energy consumption. The eontent-eentrie networking （CCN） proposed a content-centric paradigm which was proven to have higher energy efficiency. Based on the energy optimization model of CCN with in-network caching, the authors derive expressions to tradeoff the caching energy and the transport energy, and then design a new energy efficiency cache scheme based on virtual round trip time （EV） in CCN. Simulation results show that the EV scheme is better than the least recently used （LRU） and popularity based cache policies on the network average energy consumption, and its average hop is also much better than LRU policy.