Cooperative Multilayer Edge Caching in Integrated Satellite-Terrestrial Networks

As devices for the Internet of Things (IoT) are typically battery-powered, energy efficiency is a major challenge for IoT networks. In this paper, we leverage the in-network caching of Information-Centric Networking (ICN) to propose a novel cooperative caching scheme, based on the IoT data lifetime and user request rate, to improve the energy efficiency of IoT networks. By caching IoT data at different nodes (such as content routers, base stations, etc.), IoT devices can stay in sleep mode for a larger portion of time and therefore reduce the overall energy consumption. With the help of an auto- configuration mechanism, the proposed IoT data Lifetime-based Cooperative Caching (LCC) scheme can dynamically adapt to the change of request rate. Extensive evaluations were performed and the simulation results show that LCC outperforms existing schemes in terms of total energy consumption reduction (up to 40%) and the reduction in the average number of hops traversed along the path (up to 20%), which is also directly related to the response time. Keywords- Internet of Things (IoT), Cooperative Caching, Information-Centric Network (ICN).

In this paper we propose a cluster-based cooperative caching scheme for Mobile Ad Hoc Networks (MANETs). We also adopt a prefetching scheme to complement the caching scheme. A cross-layer design approach is employed to further improve the performance of cooperative caching and prefetching schemes. Cross-layer information is shared among network protocol layers. The effect of network size and the Time-To-Live value on network performance was investigated using simulation. Experimental results demonstrate that the proposed scheme improves caching performance in terms of data accessibility, query delay and query distance compared to the caching scheme that does not adopt the cooperative caching strategy.

Several protocols have been proposed to improve data accessibility in MANETs. Some of these proposals have adopted the cooperative caching scheme, allowing multiple mobile hosts within a neighborhood to cache and share data items in their local caches. Cross-layer optimization has not been fully exploited to further improve the performance of cooperative caching in these proposals. In this paper, we propose a cluster-based cooperative caching scheme which uses a cross-layer design approach and prefetching to further improve the performance of cooperative caching scheme. The cross-layer information is maintained in a separate data structure and is shared among network protocol layers. The performance evaluation was carried out in the NS-2 simulation environment and the results show that the proposed approach improves system performance.

Network coding has been proven as a very promising technique to improve wireless network throughput and energy-efficiency (EE). Meanwhile, cooperative caching, which allows the sharing and coordination of cached data among multiple nodes, can improve the performance of data access. In this paper, we aim at exploiting the potential benefits brought by cooperative caching for the multi-rate wireless networks, which have been applied to network coding scheme. We propose a cooperative caching scheme combining network coding technique, called NC-COCA, which exploits the cache spaces of relatively idle MHs, and performs encoding operation to utilize the restricted cache resource with the potential gain of network coding. Simulation results based on NS-2 demonstrate that NC-COCA can effectively improve the cache hit ratio and decrease the average retrieval delay, and the improvement of data accessibility comes from the sacrifice of messages overhead.

Device-to-device (D2D)caching has recently been proposed as a promising solution to alleviate the traffic burden for cellular networks. In such D2D caching-enabled networks, the cache strategy including where to cache and how to cache has a substantial impact on the system performance in terms of traffic offloading. In this paper, we propose a comprehensive cooperative caching strategy based on deep learning and social relationship, aiming at effectively reducing the traffic load of D2D cellular networks. An optimization problem is formulated to maximize the data offloading ratio by finding appropriate caching nodes and designing content placement strategies. To find the solution, a heuristic algorithm including content request prediction and content placement is developed. For content request prediction, we propose a method based on the neural network collaborative filtering (NCF)algorithm, which can improve the prediction accuracy by fusing recommendation algorithm and deep learning. For content placement, we develop a multi-user cooperative caching mechanism based on the social relationship and user activity level. Simulation results demonstrate that the proposed caching policy can achieve effective data offloading.

Caching of frequently accessed data in ad hoc networks is a potential technique that can improve the data access performance and availability. Cooperative caching, which allows the sharing and coordination of cached data among clients, can further explore the potential of the caching techniques. In this paper, we propose a novel scheme, called zone cooperative (ZC) for caching in mobile ad hoc networks. In ZC scheme, one-hop neighbors of a mobile client form a cooperative cache zone since the cost for communication with them is low both in terms of energy consumption and message exchange. For a data miss in the local cache, each client first searches the data in its zone before forwarding the request to the next client that lies along routing path towards server. As a part of cache management, cache admission control and replacement policy are developed to improve the data accessibility and reduce the local cache miss ratio. Simulation experiments show that the ZC caching mechanism achieves significant improvements in terms of cache hit ratio and average query latency in comparison with other caching strategies

Space-Ground Integrated Networks (SGINs) hold the potential to enable seamless and high-quality global coverage in an economically viable manner. However, the limited bandwidth and relatively long delay of satellite-ground links pose significant challenges in meeting the increasing demands driven by surging traffic. To address this issue, we propose a three-tier cooperative caching architecture incorporating base stations (BSs), satellites, and a content server, which aims to reduce the average content retrieval delay through cooperative caching between BSs and satellites. The joint optimization problem among them is both challenging to solve and non-scalable due to its exponentially increasing computational complexity. Meanwhile, the geographic characteristics of requests are overlooked in existing work. As a consequence, we propose a novel block partitioning algorithm based on the popularity similarity across areas to facilitate cooperative caching, which reduces the computational complexity, and ensures the scalability and the effectiveness of cooperative caching. Based on the partitioned blocks, the optimization problem is decomposed into two subproblems: intra-block cooperative optimization among BSs and inter-block cooperative optimization among satellites, effectively catering to the characteristics of wide-area coverage in SGINs. For the subproblems with finite dimensions, Semidefinite Relaxation (SDR) based intra-block and inter-block cooperative caching approaches are proposed to obtain the optimal cooperative caching strategies. Extensive simulations demonstrate that, compared to directly solving the original problem, the proposed algorithm reduces the solving time from exponential to linear growth. Moreover, our algorithm outperforms existing schemes by reducing 13% average retrieval delay and improving 12% overall cache hit rate.

Content Centric Mobile Ad-hoc NETwork (CCMANET) applies the advantages of Content Centric networking (CCN) into Mobile Ad Hoc Network(MANET) to overcome the drawbacks of low efficiency and unstable in transmission. Caching scheme is one of the key components of CCMANET. However, the caching scheme in CCMANET has not been well explored. In this paper, a novel cooperative caching scheme based on generalized dominating set and local content popularity for CCMANET is proposed. First, a virtual backbone in CCMANET is constructed by generalized dominating set to make the arbitrary topology become two-level hierarchy and a collaborative cache placement scheme between the two hierarchies is designed. Second, we propose a method of computing the local content popularity and a cache replacement scheme based on the local content popularity. Simulation results show that the proposed caching scheme can effectively reduces both path stretch value and server load, and improves the hit ratio compared with the existing caching schemes.

Caching of frequently accessed data in multi-hop ad hoc environment is a potential technique that can improve the data access performance and availability. Cooperative caching, which allows the sharing and coordination of cached data among clients, can further explore the potential of the caching techniques. In this paper, we propose a novel scheme, called zone cooperative (ZC) for caching in mobile ad hoc networks. In ZC scheme, one-hop neighbors of a mobile client form a cooperative cache zone since the cost for communication with them is low both in terms of energy consumption and message exchange. As a part of cache management, cache admission control and VALUE based replacement policy are developed to improve the data accessibility and reduce the local cache miss ratio. An analytical study of ZC based on data popularity, node density and transmission range is also performed. Simulation experiments show that the ZC caching mechanism achieves significant improvements in cache hit ratio and average query latency in comparison with other caching strategies.

Cooperative caching in the device-to-device (D2D) networks is an effective solution to the problem of offloading data traffic at peak times. However, one of the main challenges of cooperative caching is the selfish nature of the user, and some users only cache what they are interested in and don't care about other people's needs. In this paper, we investigate a physical-social-based cooperative caching framework, considering the physical-social tie as a non-monetary incentive to motivate the data cache and share between users by using D2D communication. Specifically, we first define a novel physical-social tie, combining the physical factors and social relationship. After that, we formulate two mathematical programming models with or without the consideration of indirect physical-social tie, to find an optimal caching strategy with the target of maximizing the social group utility. Moreover, we adopt Six Degrees of Separation to analyze the indirect physical-social tie between users when these social users with direct physical-social tie cannot meet the date request of the user, and then devise an indirect social group formation algorithm (ISGFA) to obtain the indirect social group of the user. Finally, simulation results shows that the caching scheme obtained from our model is efficient and outperforms other caching schemes that without considering the physical-social tie.

Caching content of small base stations (SBSs) is a promising approach in the fifth generation (5G) wireless networks for decreasing the transmission delay and energy consumption. The key issue in caching is effective cooperation among SBSs for full usage of the caching to reduce the systems cost. In this paper, we first introduce the architecture of wireless cellular networks with caching in 5G. We divide the caching space into two parts: One caches the fixed content purchased by telecom operators from the remote service providers, and the other one caches contents for wireless transmission. Then, we propose the cooperative caching scheme based on content-exchanged, where each user can get its demanded data from either local SBS or purchasing the contents stored in the neighboring cooperative SBSs. We further prove the concavity of system costs regarding to the proportion between the two parts. We also propose a mechanism to search for the minimal system costs. Finally, by simulations, we prove that the performance of our proposed cooperative caching scheme is better than that of the traditional cache schemes without purchasing the contents between SBSs.

Information-centric network emphasizes on translating the current Internet paradigm from host driven to content driven. A numerous data-centric features like content driven routing, random network topology, and pervasive caching make ICN caching distinct from state of the art of work. This paper emphasizes on the cooperative caching in ICN and contributes a dominating-set-oriented cooperative caching strategy. It considers placement of data and request message forwarding in a strong co-relation. Here, the concept of connected dominating set has been used to create a virtual backbone that includes core routers where most popular content can be cached. The betweenness centrality parameter of that core router helps the routing strategy to forward request packet to the node where content is most likely to be stored which leads to faster retrieval of data. The proposed strategy will improve the performance parameters like content retrieval latency, cache hit ratio, mean hop distance, total transportation cost, and network overhead. The paper also discusses the working of proposed strategy with related algorithms, illustrations, and its benefits over state-of-the-art research in context of network performance.KeywordsConnected dominating setBetweenness centralityCooperative cachingRequest forwardingInformation centric networks

The past decade has experienced a continued increase in the popular use of Web services. Unfortunately, the growth of Web services, coupled with their their role as a vital source of news and information has lead to many well published sources of stress that tend to cripple performance at both the client and the server side [1, 4]. Our work considers one such type of stress, called a flash crowd. A flash crowd arrives as a tidal wave, where the initial (and largest) spike in traffic generally occurs within the first few minutes. This gives client and servers only a few tens of seconds to adapt to the incoming traffic! In addition, flash crowds are infrequent and unpredictable. Hence, any solution deployed to mitigate flash crowd must consist of: (1) proactive and real-time mechanisms to detect the flash crowd while (or even before) it happens, and (2) an initiation of immediate action that can mask the effects of the stress.A variety of system designs for content delivery have emerged over the past few years. Based on their underlying design methodologies, we classify these existing designs into four classes. We use this taxonomy to compare the effectiveness of the existing designs to mitigate flash crowds. The four classes are: (1) Single server solutions that target core server performance, such as SEDA [6]; (2) Server cooperation solutions that distribute content through cooperation amongst multiple servers, such as Coral [2]; (3) Server-Client solutions that require changes to the behavior of both the client and server side, such as Overhaul [5]; (4) Client cooperative caching solutions that utilize peer-to-peer routing substrates, such as Squirrel [3].We follow a four-step approach in our study of flash crowds:• Characteristics of flash crowds: We study the properties of six real flash crowds based on traces collected from the respective websites.• Real-time Flash Crowd Detector: We present the design and implementation of a real-time stochastic detector of flash crowds, running at the server. A detector must continuously monitor visitor traffic and resource utilization, and be able to immediately and accurately flag a flash crowd in real-time. Additionally, the detector must run efficiently, without consuming significant computational and memory resources, especially during normal operations. We find that our design enables us to detect a flash crowd while the event is happening.• Comparison of existing solutions: We use flash crowd traces to compare the effectiveness of three of the four methodologies discussed above. We measure both network utilization of the server (a resource which directly affects the content provider's costs) and the quality of service as perceived by the clients (i.e., the turnaround latency for each request).• Design of an Adaptive Cooperative Caching Solution: We combine our real-time flash crowd detector at the server, with a cooperative caching scheme among clients, to design an adaptive cooperative caching solution for flash crowds. We compare the performance of this scheme with the existing methodologies. Our results reveal that such an approach is extremely effective in turning a flash crowd into a smart mob.

This paper presents CMP Cooperative Caching, a unified framework to manage a CMP's aggregate on-chip cache resources. Cooperative caching combines the strengths of private and shared cache organizations by forming an aggregate "shared" cache through cooperation among private caches. Locally active data are attracted to the private caches by their accessing processors to reduce remote on-chip references, while globally active data are cooperatively identified and kept in the aggregate cache to reduce off-chip accesses. Examples of cooperation include cache-to-cache transfers of clean data, replication-aware data replacement, and global replacement of inactive data. These policies can be implemented by modifying an existing cache replacement policy and cache coherence protocol, or by the new implementation of a directory-based protocol presented in this paper. Our evaluation using full-system simulation shows that cooperative caching achieves an off-chip miss rate similar to that of a shared cache, and a local cache hit rate similar to that of using private caches. Cooperative caching performs robustly over a range of system/cache sizes and memory latencies. For an 8-core CMP with 1MB L2 cache per core, the best cooperative caching scheme improves the performance of multithreaded commercial workloads by 5-11% compared with a shared cache and 4-38% compared with private caches. For a 4-core CMP running multiprogrammed SPEC2000 workloads, cooperative caching is on average 11% and 6% faster than shared and private cache organizations, respectively.

The combination of underlay spectrum sharing and coordinated multi-point technologies promises substantial spectral efficiency (SE) gains for 5G cellular networks. In this work, we present a family of simple cooperative mobile edge caching strategies that create joint transmission (JT) opportunities and make use of the non-computational-demanding score-gated least recently used (SG-LRU) caching scheme to achieve high cache hit rate, thus increasing the sum-SE and reducing both the backhaul traffic and the content access latency. In addition, we derive a low-complexity coordinated quality-of-service (QoS) aware resource allocation scheme that maximizes the sum-SE of coordinated beamforming (CBF) under given transmission power per base station, inter-system interference power, and per-user QoS constraints as well as simple alternatives for both CBF and JT. We consider a use case where a cellular network coexists with a fixed satellite service earth station in the 3.7-4.2 GHz C-band. Numerical simulations illustrate the performance gains of the proposed coordinated caching and resource allocation strategies and shed light on the impact of various parameters on their efficiency.