Caching System Research Articles

New storage and data access solution for CMS experiment in Spain towards HL-LHC era

The Large Hadron Collider (LHC) will enter a new era for data acquisition by 2029 within the High-Luminosity Large Hadron Collider (HL-LHC) program, where the LHC will raise the proton and ion collisions up to unprecedented levels. This increase will imply a factor 10 in terms of luminosity as compared to the current values, having an impact in the way the experimental data is stored and analyzed. This work focuses on the research and development of new data cache solutions that are adopted towards the new era, studying its effects at the Spanish WLCG sites that support CMS activities, namely the PIC Tier-1 and CIEMAT Tier-2. We propose a model to access and cache the most popular CMS datasets in Spain by deploying XCache cache systems in both PIC and CIEMAT sites. This work is complemented with dedicated studies to better understand and optimize these new solutions in the region.

A Low-Latency and High-Endurance MLC STT-MRAM-Based Cache System

Spin-transfer torque magnetic random access memory (STT-MRAM) is a promising cache memory candidate due to its high density, low leakage power, and nonvolatility. Multilevel cell (MLC) STT-MRAM can further increase density by storing 2 bits in one cell’s hard and soft domain, respectively. However, MLC STT-MRAM suffers two-step write, leading to high write energy, long latency, and severe lifetime degradation. Current encoding techniques propose to encode the new data to reduce the two-step data writes. However, they have two weaknesses: 1) high area overhead, e.g., recent work TSE (Hsieh et al., 2020) needs extra 37.5% MLCs and 2) prolong the write latency due to an extra read. Therefore, we propose enhanced one-step write (EOSwrite) to write data in one step. EOSwrite includes line bypassing and four intraline encoding techniques. Line bypassing schemes can bypass the writes to zero or clean lines, leading to low write/read latency. As for the intraline techniques, we propose four write modes. They utilize the data patterns and the clean data in cache lines to write data in one step, therefore reducing the data write latency. The key idea of one-step write is to write as much data as possible in the soft domain of MLC STT-MRAM. EOSwrite can greatly relieve the weaknesses of the current encoding schemes. Evaluation results show that EOSwrite can improve the lifetime of MLC STT-MRAM by 56.96%, reduce dynamic energy by 33.95%, reduce access latency by 36.95%, and improve system performance of MLC STT-MRAM by 4.30%, respectively. While the area overhead of EOSwrite is only 7.27%.

SpecBox: A Label-Based Transparent Speculation Scheme Against Transient Execution Attacks

Speculative execution techniques have been a cornerstone of modern processors to improve instruction-level parallelism. However, recent studies showed that this kind of techniques could be exploited by attackers to leak secret data via transient execution attacks, such as Spectre. Many defenses are proposed to address this problem, but they all face various challenges: (1) Tracking data flow in the instruction pipeline could comprehensively address this problem, but it could cause pipeline stalls and incur high performance overhead; (2) Making side effect of speculative execution imperceptible to attackers, but it often needs additional storage components and complicated data movement operations. In this article, we propose a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">label-based transparent speculation</i> scheme called <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SpecBox</small> . It dynamically partitions the cache system to isolate speculative data and non-speculative data, which can prevent transient execution from being observed by subsequent execution. Moreover, it uses thread ownership semaphores to prevent speculative data from being accessed across cores. In addition, <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SpecBox</small> also enhances the auxiliary components in the cache system against transient execution attacks, such as hardware prefetcher. Our security analysis shows that <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SpecBox</small> is secure and the performance evaluation shows that the performance overhead on SPEC CPU 2006 and PARSEC-3.0 benchmarks is small.

A Hybrid Proactive Caching System in Vehicular Networks Based on Contextual Multi-Armed Bandit Learning

Proactive edge caching has been regarded as an effective approach to satisfy user experience in mobile networks by providing seamless content transmission and reducing network delay. This is particularly useful in rapidly changing vehicular networks. This paper addresses the proactive edge caching (at the roadside unit (RSU)) problem in vehicular networks by mobility prediction, i.e., the next RSU prediction. Specifically, the paper proposes a distributed <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Hybrid cMAB Proactive Caching System</i> where RSUs act as independent learners that implement two parallel online reinforcement learning-based mobility prediction algorithms between which they can adaptively finalize their predictions for the next RSU. The two parallel prediction algorithms are based on <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Contextual Multi-armed bandit</i> (cMAB) learning, called <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Dual-context cMAB</i> and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Single-context cMAB</i> . The hybrid system is further developed into two variants: <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Vehicle-Centric</i> and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">RSU-Centric</i> . In addition, the paper also conducts comprehensive simulation experiments to evaluate the prediction performance of the proposed hybrid system. They include three traffic scenarios: <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Commuting traffic, Random traffic</i> and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Mixed traffic</i> in Las Vegas, USA and Manchester, UK. With the different road layouts in the two urban areas, the paper aims to generalize the application of the system. Simulation results show that the hybrid Vehicle-Centric system can reach nearly 95% cumulative prediction accuracy in the Commuting traffic scenario and outperform the other methods used for comparison by reaching nearly 80% accuracy in Mixed traffic scenario. Even in the completely Random traffic scenario, it also guarantees a minimum accuracy of nearly 60%.

Design and Implement of High-speed Receiving Cache System of the Satellite

遥感卫星图像数据量的高速增长，以及遥感卫星搭载的相机不同工作模式下产生的数据差异化处理的需求，为星间数据处理带来了巨大挑战。针对星载Gbit·s^–1级高速数据收发及文件缓存等星间数据处理面临的问题，以百兆每秒级星载高速接收缓存系统为切入点，以遥感卫星数据处理的发展为依据，在分析SerDes传输原理的基础上，采用模型仿真和工程验证的方法，制定了高速串行数据链路层传输协议SSLLP（Satellite Serial Link Layer Protocol）和类文件化高速缓存的策略。在硬件设计和软件开发的基础上，最终完成了具备处理入口速率3.2 Gbit·s^–1并能以类文件化的方式缓存64个数据文件的星载数据处理单元的工程实现。测试结果表明，基于SSLLP的高速串行数据接收正确，缓存策略有效，系统高效可靠。该设计已在某型号任务中取得在轨验证，为星载高速串行数据处理系统提供了参考。

Ether-IoT: A Realtime Lightweight and Scalable Blockchain-Enabled Cache Algorithm for IoT Access Control

Several unique characteristics of Internet of Things (IoT) devices, such as distributed deployment and limited storage, make it challenging for standard centralized access control systems to enable access control in today’s large-scale IoT ecosystem. To solve these challenges, this study presents an IoT access control system called Ether-IoT based on the Ethereum Blockchain (BC) infrastructure with Attribute-Based Access Control (ABAC). Access Contract (AC), Cache Contract (CC), Device Contract (DC), and Policy Contract (PC) are the four central smart contracts (SCs) that are included in the proposed system. CC offers a way to save user characteristics in a local cache system to avoid delays during transactions between BC and IoT devices. AC is the fundamental program users typically need to run to build an access control technique. DC offers a means for storing the resource data created by devices and a method for querying that data. PC offers administrative settings to handle ABAC policies on users’ behalf. Ether-IoT, combined with ABAC and the BC, enables IoT access control management that is decentralized, fine-grained and dynamically scalable. This research gives a real-world case study to illustrate the suggested framework’s implementation. In the end, a simulation experiment is performed to evaluate the system’s performance. To ensure data integrity in dispersed systems, the results show that Ether-IoT can sustain high throughput in contexts with a large number of requests.

Heterogeneous Edge Caching Based on Actor-Critic Learning With Attention Mechanism Aiding

In recent years, the explosive growth of network traffic has placed significant strain on backbone networks. To alleviate the content access delay and reduce additional network resource consumption resulting from large-scale requests, edge caching has emerged as a promising technology. Despite capturing substantial attention from both academia and industry, most existing studies overlook the heterogeneity of the environment and the spatial-temporal characteristics of content popularity. As a result, the potential for edge caching remains largely unexploited. To address these challenges, we propose a neighborhood-aware caching (NAC) framework in this paper. The framework leverages the perimeter information from neighboring base stations (BSs) to model the edge caching problem in heterogeneous scenarios as a Markov Decision Process (MDP). To fully exploit the environmental information, we introduce an improved actor-critic method that integrates an attention mechanism into the neural network. The actor-network in our framework is responsible for making caching decisions based on local information, while the critic network evaluates and enhances the actor's performance. The multi-head attention layer in the critic network enables integration of environmental features into the model, reducing the limitations associated with local investigation. To facilitate comparison from an engineering perspective, we also propose a heuristic algorithm, Neighbor-Influence-Least-Frequently-Use (NILFU). Our extensive experiments demonstrate that the proposed NAC framework outperforms other baseline methods in terms of average delay, hit rate, and traffic offload ratio in heterogeneous scenarios. This highlights the effectiveness of the neighborhood-aware caching approach in enhancing the performance of edge caching systems in such scenarios.

A Performance Evaluation of In-Memory Databases Operations in Session Initiation Protocol

Real-time communication has witnessed a dramatic increase in recent years in user daily usage. In this domain, Session Initiation Protocol (SIP) is a well-known protocol found to provide trusted services (voice or video) to end users along with efficiency, scalability, and interoperability. Just like other Internet technology, SIP stores its related data in databases with a predefined data structure. In recent, SIP technologies have adopted the real advantages of in-memory databases as cache systems to ensure fast database operations during real-time communication. Meanwhile, in industry, there are several names of in-memory databases that have been implemented with different structures (e.g., query types, data structure, persistency, and key/value size). However, there are limited resources and poor recommendations on how to select a proper in-memory database in SIP communications. This paper provides recommended and efficient in-memory databases which are most fitted to SIP servers by evaluating three types of databases including Memcache, Redis, and Local (OpenSIPS built-in). The evaluation has been conducted based on the experimental performance of the impact of in-memory operations (store and fetch) against the SIP server by applying heavy load traffic through different scenarios. To sum up, evaluation results show that the Local database consumed less memory compared to Memcached and Redis for read and write operations. While persistency was considered, Memcache is the preferable database selection due to its 25.20 KB/s for throughput and 0.763 s of call–response time.

Formulating Cost-Effective Data Distribution Strategies Online for Edge Cache Systems

Edge Computing (EC) enables a new kind of caching system in close geographic proximity to end-users by allowing app vendors to cache popular data on edge servers deployed at base stations. This edge cache system can better support latency-sensitive applications. However, transmitting data from the centralized cloud to the edge servers without proper transmission strategies may cost app vendors dearly. Cost-effective data distribution strategies are of particular importance for applications, whose data to be cached at the edge often changes dynamically. In this paper, we study this <i>Online Edge Data Distribution</i> (OEDD) problem, aiming to minimize app vendors’ total transmission cost, while ensuring low transmission latency in the long term. We first model this problem and prove its <inline-formula><tex-math notation="LaTeX">$\mathcal {NP}$</tex-math></inline-formula> -hardness. We then combine Lyapunov optimization and game theory to propose a novel Latency-Aware Online (LAO) approach for solving this OEDD problem over time in a distributed manner with provable performance guarantees. The evaluation of LAO based on a real-world dataset demonstrates that it can help app vendors formulate cost-effective edge data distribution strategies in an online manner.

False Negative Awareness in Indicator-Based Caching Systems

Distributed caching systems such as content distribution networks often advertise their content via lightweight approximate indicators (e.g., Bloom filters) to efficiently inform clients where each datum is likely cached. While false-positive indications are necessary and well understood, most existing works assume no false-negative indications. Our work illustrates practical scenarios where false-negatives are unavoidable and ignoring them significantly impacts system performance. Specifically, we focus on false-negatives induced by indicator staleness, which arises whenever the system advertises the indicator only periodically, rather than immediately reporting every change in the cache. Such scenarios naturally occur, e.g., in bandwidth-constraint environments or when latency impedes each client’s ability to obtain an updated indicator. Our work introduces novel false-negative aware access policies that continuously estimate the false-negative ratio and sometimes access caches despite negative indications. We present optimal policies for homogeneous settings and provide approximation guarantees for our algorithms in heterogeneous environments. We further perform an extensive simulation study with multiple real system traces. We show that our false-negative aware algorithms incur a significantly lower service cost than existing approaches or match the cost of these approaches while requiring an order of magnitude fewer resources (e.g., caching capacity or bandwidth).

Enabling Long-term Fairness in Dynamic Resource Allocation

We study the fairness of dynamic resource allocation problem under the α-fairness criterion. We recognize two different fairness objectives that naturally arise in this problem: the well-understood slot-fairness objective that aims to ensure fairness at every timeslot, and the less explored horizon-fairness objective that aims to ensure fairness across utilities accumulated over a time horizon. We argue that horizon-fairness comes at a lower price in terms of social welfare. We study horizon-fairness with the regret as a performance metric and show that vanishing regret cannot be achieved in presence of an unrestricted adversary. We propose restrictions on the adversary's capabilities corresponding to realistic scenarios and an online policy that indeed guarantees vanishing regret under these restrictions. We demonstrate the applicability of the proposed fairness framework to a representative resource management problem considering a virtualized caching system where different caches cooperate to serve content requests.

Memory-Rate Tradeoff for Caching With Uncoded Placement Under Nonuniform Random Demands

For a caching system with multiple users, we aim to characterize the memory-rate tradeoff for caching with uncoded cache placement, under nonuniform file popularity. Focusing on the modified coded caching scheme (MCCS) recently proposed by Yu, etal., we formulate the cache placement optimization problem for the MCCS to minimize the average delivery rate under nonuniform file popularity, restricting to a class of popularity-first placements. We then present two information-theoretic lower bounds on the average rate for caching with uncoded placement, one for general cache placements and the other restricted to the popularity-first placements. By comparing the average rate of the optimized MCCS with the lower bounds, we prove that the optimized MCCS attains the general lower bound for the two-user case, providing the exact memory-rate tradeoff. Furthermore, it attains the popularity-first-based lower bound for the case of general K users with distinct file requests. In these two cases, our results also reveal that the popularity-first placement is optimal for the MCCS, and zero-padding used in coded delivery incurs no loss of optimality. For the case of K users with redundant file requests, our analysis shows that there may exist a gap between the optimized MCCS and the lower bounds due to zero-padding. We next fully characterize the optimal popularity-first cache placement for the MCCS, which is shown to possess a simple file-grouping structure and can be computed via an efficient algorithm using closed-form expressions. Finally, we extend our study to accommodate both nonuniform file popularity and sizes, where we show that the optimized MCCS attains the lower bound for the two-user case, providing the exact memory-rate tradeoff. Numerical results show that, for general settings, the gap between the optimized MCCS and the lower bound only exists in limited cases and is very small.

Unselfish Coded Caching Can Yield Unbounded Gains Over Selfish Caching

The original coded caching scenario assumes a content library that is of interest to all receiving users. In a realistic scenario though, the users may have diverging interests which may intersect to various degrees. What happens for example if each file is of potential interest to, say, 40% of the users and each user has potential interest in 40% of the library? In this work, we investigate the so- called symmetrically selfish coded caching scenario, where each user only makes requests from a subset of the library that defines its own file demand set (FDS), each user caches selfishly only contents from its own FDS, and where the different FDSs symmetrically overlap to some extent. In the context of various traditional prefetching scenarios (prior to the emergence of coded caching), selfish approaches were known to be potentially very effective. On the other hand — with the exception of some notable works — little is known about selfish coded caching. We here present a new information-theoretic converse that proves, in a general setting of symmetric FDS structures, that selfish coded caching, despite enjoying a much larger local caching gain and a much smaller set of possible demands, introduces an unbounded load increase compared to the unselfish case. In particular, in the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula> -user broadcast channel where each user stores a fraction <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\gamma $ </tex-math></inline-formula> of the library, where each file (class) is of interest to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\alpha $ </tex-math></inline-formula> users, and where any one specific file is of interest to a fraction <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\delta $ </tex-math></inline-formula> of users, the optimal coding gain of symmetrically selfish caching is at least <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$(K - \alpha)\gamma + 1$ </tex-math></inline-formula> times smaller than in the unselfish scenario. This allows us to draw the powerful conclusion that the optimal selfish coding gain is upper bounded by <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$1/(1 - \delta)$ </tex-math></inline-formula> , and thus does not scale with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula> . These derived limits are shown to be exact for different types of demands. In the end, this work provides, in a unified manner, the strong conclusion that selfish caching can cause unbounded performance deterioration in coded caching systems.

Life on Mars (LoMars): History, advances, current research, and perspectives

A quest for life on Mars (LoMars) started in the early 1960s when the most prestigious scientific journals published several research articles. According to Elsevier’s Scopus database, the rise in annual literature production started in the late 1990s, most likely associated with the launch of the National Aeronautics and Space Administration’s (NASA) first rover, Sojourner, in 1996. The number of articles on Mars will likely continue to rise sharply, given that the launch and landing of the Mars 2020 Perseverance Rover are critical to discovering and understanding the present or past life on the planet. Thus far, the USA has dominated in the number of citations and collaborations related to Mars research, given its facilities equipped with relevant infrastructure and researchers’ capacity to explore the Solar System beyond Earth. Most of these frequently cited papers report observational and theoretical research results. However, a highly cited article is based on analytical studies of a unique Martian meteorite (i.e., Allan Hills 84001) found in Antarctica. It is expected that the future sample return mission associated with the Perseverance Rover caching system could increase the LoMars research exponentially in the coming decades if Martian samples are successfully brought to Earth. Based on the total number of publications on LoMars, the most influential institute, the author, and the journal are Caltech, C.P. McKay, and Icarus, respectively. Both the institute and the author are directly affiliated with NASA, indicating the leadership offered by the organization in LoMars research.

A New Upper Bound on Cache Hit Probability for Non-Anticipative Caching Policies

Caching systems have long been crucial for improving the performance of a wide variety of network and web-based online applications. In such systems, end-to-end application performance heavily depends on the fraction of objects transferred from the cache, also known as the cache hit probability . Many caching policies have been proposed and implemented to improve the hit probability. In this work, we propose a new method to compute an upper bound on hit probability for all non-anticipative caching policies and for policies that have no knowledge of future requests. Our key insight is to order the objects according to the ratio of their Hazard Rate (HR) function values to their sizes, and place in the cache the objects with the largest ratios till the cache capacity is exhausted. When object request processes are conditionally independent, we prove that this cache allocation based on the HR-to-size ratio rule guarantees the maximum achievable expected number of object hits across all non-anticipative caching policies. Further, the HR ordering rule serves as an upper bound on cache hit probability when object request processes follow either independent delayed renewal process or a Markov modulated Poisson process. We also derive closed form expressions for the upper bound under some specific object request arrival processes. We provide simulation results to validate its correctness and to compare it to the state-of-the-art upper bounds, such as produced by Bélády’s algorithm. We find it to be tighter than state-of-the-art upper bounds for some specific object request arrival processes such as independent renewal, Markov modulated, and shot noise processes.

Advancing caching and automation with FDO

Advancing caching and automation with FDO

Fundamental Structure of Optimal Cache Placement for Coded Caching With Nonuniform Demands

This paper studies the caching system of multiple cache-enabled users with random demands. Under nonuniform file popularity, we thoroughly characterize the optimal uncoded cache placement structure for the coded caching scheme (CCS). Formulating the cache placement as an optimization problem to minimize the average delivery rate, we identify the file group structure in the optimal solution. We show that, regardless of the file popularity distribution, there are <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">at most three file groups</i> in the optimal cache placement, where files within a group have the same cache placement. We further characterize the complete structure of the optimal cache placement and obtain the closed-form solution in each of the three file group structures. A simple algorithm is developed to obtain the final optimal cache placement by comparing a set of candidate closed-form solutions computed in parallel. We provide insight into the file groups formed by the optimal cache placement. The optimal placement solution also indicates that coding between file groups may be explored during delivery, in contrast to the existing suboptimal file grouping schemes. Using the file group structure in the optimal cache placement for the CCS, we propose a new information-theoretic converse bound for coded caching that is tighter than the existing best one. Moreover, we characterize the file subpacketization in the CCS with the optimal cache placement solution and show that the maximum subpacketization level in the worst case scales as <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${\mathcal{ O}}(2^{K}/\sqrt {K})$ </tex-math></inline-formula> for <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula> users.

Cross-User Similarities in Viewing Behavior for 360° Video and Caching Implications

The demand and usage of 360° video services are expected to increase. However, despite these services being highly bandwidth intensive, not much is known about the potential value that basic bandwidth saving techniques such as server or edge-network on-demand caching (e.g., in a CDN) could have when used for delivery of such services. This problem is both important and complicated as client-side solutions have been developed that split the full 360° view into multiple tiles, and adapt the quality of the downloaded tiles based on the user’s expected viewing direction and bandwidth conditions. This article presents new trace-based analysis methods that incorporate users’ viewports (the area of the full 360° view the user actually sees), a first characterization of the cross-user similarities of the users’ viewports, and a trace-based analysis of the potential bandwidth savings that caching-based techniques may offer under different conditions. Our analysis takes into account differences in the time granularity over which viewport overlaps can be beneficial for resource saving techniques, compares and contrasts differences between video categories, and accounts for uncertainties in the network conditions and the prediction of the future viewing direction when prefetching. The results provide substantial insight into the conditions under which overlap can be considerable and caching effective, and inform the design of new caching system policies tailored for 360° video.

A Path Load-Aware Based Caching Strategy for Information-Centric Networking

Ubiquitous in-network caching plays an important role in improving the efficiency of content access and distribution in Information-Centric Networks (ICN). Content placement strategies, which determine the location distribution of content replicas in the network, have a decisive impact on the performance of the cache system. Existing strategies primarily focus on pushing popular content to the network edge, aiming to improve the overall cache hit ratio while neglecting to effectively balance the traffic load between network links; this leads to insufficient utilization of network bandwidth resources and further excessive content delivery time and user QoE degradation. In this paper, a Path Load-Aware Based Caching strategy (PLABC) is proposed, in which content-related information and dynamic network-related information are comprehensively considered to make cache decisions. Specifically, the utility of caching the content at each on-path node is calculated according to the bandwidth consumption savings and the load level of the transmission path, and the node with the greatest utility value is selected as the caching node. Extensive simulations are conducted to compare the performance of PLABC with other state-of-the-art schemes by quantitative analysis. Simulation results validate the PLABC strategy’s effectiveness, especially in balancing link load and reducing content delivery time.

Intelligent-Reflecting-Surface-Empowered Wireless-Powered Caching Networks

In this article, we propose an intelligent reflecting surface (IRS)-enabled wireless-powered caching system. In the proposed IRS model, a power station (PS) provides wireless energy to multiple Internet of Things (IoT) devices, delivering their information to an access point (AP) by utilizing the harvested power. The AP, equipped with a local cache, stores the IoT data to avoid waking up the IoT devices frequently. Meanwhile, we deploy the IRS involving in the wireless energy and information transfer process for performance enhancements. In this practical system, the PS and AP could belong to different service providers. Also, the AP requires to incentivize the PS to offer a provisional energy service. We model the interaction between the PS and AP as a Stackelberg game that jointly optimizes the transmit power of the PS, the energy price, the phase shifts of the wireless energy transfer (WET) and wireless information transfer (WIT) phases, as well as wireless caching strategies of the AP. In this way, we first derive the optimal solutions of the phase shifts and the transmit power of the PS in a closed form. We propose an alternating optimization (AO) algorithm to optimize the wireless caching strategies and the energy price iteratively. Finally, we present various numerical evaluations to validate the beneficial role of the IRS and the wireless caching strategies and the performance of the proposed scheme compared with the existing benchmark schemes.