Information-centric mobile caching network frameworks and caching optimization: a survey <s> Cache insertion policies <s> In content-oriented networking, content files are typically cached in network nodes, and hence how to cache content files is crucial for the efficient content delivery and cache storage utilization. In this paper, we propose a content caching scheme, WAVE, in which the number of chunks to be cached is adjusted based on the popularity of the content. In WAVE, an upstream node recommends the number of chunks to be cached at its downstream node, which is exponentially increased as the request count increases. Simulation results reveal that the average hop count of content delivery of WAVE is lower than other schemes, and the inter-ISP traffic volume of WAVE is the second lowest (CDN is the lowest). Also, WAVE achieves higher cache hit ratio and fewer frequent cache replacements than other on-demand caching strategies. <s> BIB001 </s> Information-centric mobile caching network frameworks and caching optimization: a survey <s> Cache insertion policies <s> New communication protocols, as WiFi Direct, are now available to enable efficient Device-to-Device (D2D) communications in wireless networks based on portable devices. At the same time, new network paradigms, as Content-Centric-Networking (CCN), allow a communication focused on the content and not its location within the network, enabling a flexible location for the content, which can be cached in the nodes across the network. In such context, we consider a multi-hop wireless network adopting CCN-like cooperative caching, in which each user terminal acts also as a caching node. We propose an interest-based insertion policy for the caching, based on the concept of “social-distance” borrowed by online recommendation systems, to improve the performance of the overall network of caches; the main idea is to store only the contents which appear to be of interest for the local user. We show that our proposed scheme outperforms other well-known insertion policies, that are oblivious of such social-distance, in terms of cache hit probability and access delays. <s> BIB002 </s> Information-centric mobile caching network frameworks and caching optimization: a survey <s> Cache insertion policies <s> Internet usage has drastically shifted from host-centric end-to-end communication to receiver-driven content retrieval. In order to adapt to this change, a handful of innovative information/content centric networking (ICN) architectures have recently been proposed. One common and important feature of these architectures is to leverage built-in network caches to improve the transmission efficiency of content dissemination. Compared with traditional Web Caching and CDN Caching, ICN Cache takes on several new characteristics: cache is transparent to applications, cache is ubiquitous, and content to be cached is more ine-grained. These distinguished features pose new challenges to ICN caching technologies. This paper presents a comprehensive survey of state-of-art techniques aiming to address these issues, with particular focus on reducing cache redundancy and improving the availability of cached content. As a new research area, this paper also points out several interesting yet challenging research directions in this subject. <s> BIB003 </s> Information-centric mobile caching network frameworks and caching optimization: a survey <s> Cache insertion policies <s> Information-centric network (ICN) opens a new networking paradigm optimized for contents-oriented services by exploiting in-network caching and mitigating redundant transmissions. When such an ICN is deployed in mobile environments (i.e., the content provider or consumer is a mobile node), an appropriate mobility support protocol needs to be developed. Since the content consumer mobility can be tactically handled through the content consumer driven nature of ICN, the content provider mobility is investigated in this work. Specifically, we propose a proactive content pushing (PCP) scheme, in which the content provider proactively sends a set of contents that are expected to be requested in the near future to proximity ICN routers. Consequently, the PCP scheme can reduce the service disruption time owing to the content provider mobility. <s> BIB004 </s> Information-centric mobile caching network frameworks and caching optimization: a survey <s> Cache insertion policies <s> A mobile opportunistic social network (MOSN) is a new type of delay tolerant network (DTN), in which the mobile users contact each other opportunistically. While cooperative caching in the Internet has been studied extensively, cooperative caching in MOSNs is a considerably different and challenging problem due to the probabilistic nature of contact among the mobile users in MOSNs. In order to reduce the total access delay, we let the mobile users cooperatively cache these data items in their limited buffer space. We balance between selfishness (caching the data items according to its own preference) and unselfishness (helping other nodes to cache). The friends with higher contact frequency may share similar interests, hence, caching the data items for friend users can lead to some benefit. In this paper, we present a hierarchical cooperative caching scheme, which divides the buffer space into three components: self, friends, and strangers. In the self component, mobile users cache the data items according to their preference. In the friends component, mobile users help their friends to cache some data items. In the strangers component, mobile users randomly cache the remaining data items. We formally analyze the access delay of the proposed scheme. The effectiveness of our approach is verified through extensive real world trace-driven simulations. <s> BIB005 </s> Information-centric mobile caching network frameworks and caching optimization: a survey <s> Cache insertion policies <s> Information-Centric Networking (ICN) has a great potential to better support the content distribution over the future Internet. Meanwhile, users with mobile devices will also access ICN, introducing a new challenge to ICN providers to handle such mobile content requests. In this paper, a mobility and popularity-based caching strategy is proposed to increase the cache hit rate through WiFi while people are moving from one WiFi hotspot to another. It thus lowers the network traffic from the local ICN to the outside Internet. Specifically, a precise derivation on the content request rate is provided based on the content popularity and user mobility. A novel caching strategy is further developed based on this derivation for both the mobility-oblivious and mobility-aware scenarios. We evaluate different caching strategies with a trace-driven simulation and our new approach can achieve a 33.84% reduction on the network traffic when compared with the caching strategies only considering the content popularity. <s> BIB006 </s> Information-centric mobile caching network frameworks and caching optimization: a survey <s> Cache insertion policies <s> Information-Centric Networking (ICN) is a novel networking paradigm that attracts increasing research interests in recent years. In-network caching has been viewed as an attractive feature of ICN because it can reduce network traffic, alleviate server bottleneck, and reduce the user access latencies. Because of this, the network community has proposed many in-network caching mechanisms that aim at optimizing various performance metrics such as cache hit ratio and cache hit distance. In this survey, we present a comprehensive overview of the recently proposed in-network caching mechanisms for ICN. For each caching mechanism, we describe it in detail, present examples to illustrate how it works, and analyze its possible benefits and drawbacks. We also compare some typical in-network caching mechanisms through extensive simulations and discuss the remaining research challenges. <s> BIB007
Cache insertion policy refers to the strategy of cache enabled equipments to insert contents according to some factors related to routing, content popularity and social relation of the users, etc. The state-of-the-art cache insertion policies mainly consists of Caching Everything Everywhere (CEE) BIB007 (refer to "ALL-CACHE" in BIB002 ,"leave copy everywhere (LCE)"in BIB003 ), Leave Copy Down (LCD) BIB002 BIB007 BIB003 , Caching with Probability (Prob(p)) BIB002 BIB007 BIB003 , ProbCache  , WAVE BIB001 , Breadcrumbs  , Ditto Ad hoc based network Edge based caching( in every node and in the server) [42-48, 59, 89, 92] Hybrid network Edge based caching (in APs, BSs and mobile devices) [3, 5, 7, 49, 51-55, 85, 86, 122] [59], Partial Cache  , Interest-based cooperative caching (ICC) BIB002 , Proactive Content Pushing Scheme (PCP) BIB004 , Hierarchical Cooperative Caching(HCC) BIB005 and Mobility/Popularity-Based Caching Strategy(MPCS) BIB006 ,etc. The principles of the cache insertion policies are summarized below. CEE: CEE is the default cache decision policy in CCN/NDN, and it aims to reduce user access latency and frequent downloading from the original content servers. In CEE, a requester sends out an Interest packet which is forwarded to the server, and Data packet flows back along the reverse path and it is cached at every CR along the path. It is clear that this approach is simple but has the disadvantage of caching redundancy because every CR holds the copy of the Data packet, which causes the low utilization of caching resource. LCD:LCD is designed to reduce caching redundancy in ICN. In LCD, a caching suggestion flag bit is added at the Data packet header whose state determines whether CRs along the downloading path should cache the Data packet. When a cache hit occurs in a cache node, only its direct downstream node caches the content, which prevents other CRs along the downloading path from caching the same object. The frequently requested contents tend to be cached in CRs close to end users. Therefore, LCD is a cooperative policy which considers the contents' access frequencies. Prob(p): Prob(p) is used to reduce caching redundancy and improve cache efficiency. In Prob(p), cache decision is made for each CR along the downloading path with probability p, which means each CR does not cache the requested content with probability 1-p, then if a content is requested for many times, the probability that all CRs do not cache the content is low, namely, popular contents are more likely to be cached in routers in this scheme. ProbCache:ProbCache aims to reduce caching redundancy and achieve efficient utilization of available cache resources along a delivery path. For each CR, the probability of caching incoming chunks is influenced by caching capability of paths and the distance between the CR and the user. The probability is proportional to the caching capability of the CR and inversely proportional to the distance between the CR and the user. If a CR with a big cache is close to the user, the probability of caching contents is high, while if a CR with a small cache is far from the user, the chance to cache incoming contents is little. The scheme guarantees fair load distribution and fair content flow multiplexing between contents that travel to different destinations in terms of path length. WAVE: In WAVE, contents are segmented into chunks. The number of chunks to be cached is adjusted based on the popularity of the content. An upstream node recommends the number of chunks to be cached to its downstream CRs by adding caching suggestion flag bit in data packets in order to help them make caching decisions. Breadcrumbs: Breadcrumbs aims at efficiently utilizing content caches located outside of the default path. When a content request arrives at a content server and a content is downloaded, each router along the download path stores a pointer called Breadcrumbs. This pointer points to the direction in which the content was sent. When a content request eventually encounters Breadcrumbs for the corresponding content along the default path, it is redirected towards Breadcrumbs direction. Ditto: It is an on-path opportunistic caching policy which caches overheard data at the granularity of small chunks to improve subsequent transfer throughput and reduce traffic load on the gateways in wireless mesh networks. If user i requests a video object but it can not be hit by nearby routers, then the request is sent to the gateway node, the gateway node returns the video object on the reverse path. Ditto caches the object at routers on the path, and it also overhears and caches part of the video at routers which are off the path within radio range of routers on the path. If user j subsequently requests the same video file, the request can be satisfied by the routers in radio range which overhears the transfer instead of traveling multiple hops to the gateway node. Partial Cache: It is also a chunk based caching policy in NDN. In partial cache policy, the requested content is divided into several data chunks and transmitted along the routing path, and when a user requests a multimedia named content published by a provider, the multimedia content can be partially cached in an intermediate node or a proxy node. That is to say, each neighboring node partially caches different chunks of named multimedia content. In fact, the grouped neighboring NDN nodes will keep a whole cache of named multimedia content in order to serve the next same content request from the neighboring region. ICC: It is a caching insertion policy used in multi-hop wireless networks which only stores those contents that would be of possible interest for the corresponding user according to the social distance which is defined as the Euclidean distance of the user u and the content c. Since online recommendation systems provide models to evaluate similarity of interests among users and the user's interest for a content based on the behavior of the user, the insertion policy of ICC at user u's cache simply stores the content c if their social distance is below a threshold. PCP: It is a caching insertion policy in NDN to reduce the service disruption time due to the content provider mobility. In PCP, interest and data packets are exchanged between the content providers and content consumers. When a handover trigger is detected by the content provider, the content provider sends an unsolicited DATA packet containing the selected contents for pushing. Then, the NDN routers receive the pushed contents and store the contents in their content caches. After completing the handover, the content consumer sends an interest packet. Since the requested content has been already pushed to NDN routers, the content consumer can retrieve the content from the NDN routers instead of the content provider. HCC: It is a caching insertion policy based on the social relations with the mobile user. The cache space is divided into three levels: namely self cache space, friends' cache space and strangers' cache space. The self cache space is used for the mobile user to store the data items according to his/her preference. The friends' cache space is remained to help his/her friends to cache some data items, and the strangers' cache space is for the mobile user to store cache data items randomly. MPCS: It often happens in the real world that users leave one site without finishing the current download due to the large size of contents (e.g. a video clip). On the movements between sites, users usually turn on cellular network interface to continue downloading, and may switch to Wi-Fi networks when arriving at the next hotspot. For the unfinished download, a request for the same content will be generated at the new site. In this case, these requests are dependent on the download at the previous sites, thus the content request rate at each site is affected by other sites due to the user mobility. By taking advantage of both the popularity of contents and the mobility pattern of users for ICN, MPCS consists of two caching strategies, one is called MOC(Mobility-Oblivious Caching), in which the most popular contents at any site will be cached locally to get an optimized cache hit rate, and the other is called MAC(Mobility-Aware Caching), in which the cached contents are chosen from the popularity rank list considering both the popularity ranks and the site transition matrix of mobile users. From the schemes of the caching insertion policies surveyed above, the features of the policies differentiate in content granularity, content popularity, mobility support, complexity and cooperation among cache-enabled network elements. Table 2 illustrates the comparison of different cache insertion policies.