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Many specific problems ranging from theoretical probability to applications in statistical physics, combinatorial optimization and communications can be formulated as an optimal tuning of local parameters in large systems of interacting particles. Using the framework of stationary point processes in the Euclidean space, we pose it as a problem of an optimal stationary marking of a given stationary point process. The quality of a given marking is evaluated in terms of scores calculated in a covariant manner for all points as a function of the proposed marked configuration. In the absence of a total order of the configurations of scores, we identify intensity-optimality and local optimality as two natural ways for defining optimal stationary marking. We derive tightness and integrability conditions under which intensity-optimal markings exist and further stabilization conditions making them equivalent to locally optimal ones. We present examples motivating the proposed, general framework. Finally, we discuss various possible approaches leading to uniqueness results. [ABSTRACT FROM AUTHOR]

Connected vehicles will enable the smart and autonomous transportation systems in the future. Cellular Vehicle-to-Everything (C-V2X) communication will provide wireless connectivity to enable large number of connected vehicle applications. Vehicles will receive traffic and infotainment contents from the city traffic command center using C-V2X communications. In this context, infrastructure Road Side Units (RSUs) will cache urgent and popular data in their memory storage, hence providing vehicles to retrieve information from a closer vicinity at a RSU. In this paper, we present a content caching policy for the connected vehicles operator to improve the efficiency of the content retrieval in terms of download rate and delay. We propose the utility functions for the RSUs and vehicles to cache a particular content at a given RSU. Moreover, Gale-Shapley stable matching algorithm is used to efficiently allocate RSU cache to the contents. We also provide rules to update the cache slots. The proposed caching scheme is compared with random caching policy and market matching based caching policies. Results show that the proposed content caching policy improves the efficiency of the content retrieval with 60 % more data transmission with reduced downloading time and better link utilization as compared to other two scheme. [ABSTRACT FROM AUTHOR]

Caching is an essential component of Named Data Networking (NDN), enabling efficient and scalable content distribution for future networks. The caching strategy regulates content distribution by deciding which network nodes are most suited to store duplicates of popular data. Hence, cache placement decisions are crucial to the NDN cache strategy. According to a prior study, caching decisions should consider the availability of cache storage for each node, the network's structure, and the content's popularity. However, all those criteria are not considered simultaneously in the decision-making process. Ignoring critical criteria can lead to destructive and ineffective decisions. Multi-criteria decision-making (MCDM) improves NDN efficiency in caching decisions. This paper introduces C3CPS, a novel caching placement strategy based on MCDM using CoCoSo and CRITIC weighting method for enhanced content distribution. C3CPS considers five criteria, including two related to the network topologies, two related to cache storage, and the popularity of the content. Then, C3CPS examines these criteria with the CRITIC method to determine the weight of each criterion and the CoCoSo method to determine the optimal cache node. The ICARUS simulator validates C3CPS. The results show that the C3CPS outperforms other alternative caching techniques on cache hit rate, latency, and path stretch. [ABSTRACT FROM AUTHOR]

A popular distinction in the human and animal learning literature is between deliberate (or willed) and habitual (or automatic) modes of control. Extensive evidence indicates that, after sufficient learning, living organisms develop behavioural habits that permit them saving computational resources. Furthermore, humans and other animals are able to transfer control from deliberate to habitual modes (and vice versa), trading off efficiently flexibility and parsimony – an ability that is currently unparalleled by artificial control systems. Here, we discuss a computational implementation of habit formation, and the transfer of control from deliberate to habitual modes (and vice versa) within Active Inference: a computational framework that merges aspects of cybernetic theory and of Bayesian inference. To model habit formation, we endow an Active Inference agent with a mechanism to "cache" (or memorize) policy probabilities from previous trials, and reuse them to skip – in part or in full – the inferential steps of deliberative processing. We exploit the fact that the relative quality of policies, conditioned upon hidden states, is constant over trials; provided that contingencies and prior preferences do not change. This means the only quantity that can change policy selection is the prior distribution over the initial state – where this prior is based upon the posterior beliefs from previous trials. Thus, an agent that caches the quality (or the probability) of policies can safely reuse cached values to save on cognitive and computational resources – unless contingencies change. Our simulations illustrate the computational benefits, but also the limits, of three caching schemes under Active Inference. They suggest that key aspects of habitual behaviour – such as perseveration – can be explained in terms of caching policy probabilities. Furthermore, they suggest that there may be many kinds (or stages) of habitual behaviour, each associated with a different caching scheme; for example, caching associated or not associated with contextual estimation. These schemes are more or less impervious to contextual and contingency changes. [ABSTRACT FROM AUTHOR]

The deployment of unmanned aerial vehicle (UAV)-mounted base stations is emerging as an effective solution for providing wireless communication service to ground terminals (GTs) which have failed to be associated with ground base stations for some reason. Meanwhile, with the propose of reducing the transmission latency and easing the load of backhaul links between UAVs and the core network, UAVs are equipped with the ability of caching popular contents in the storage of base stations. In this paper, we investigate the efficient deployment problem of UAVs (such as transmitting power, number of UAVs, locations and caching) while guaranteeing the quality of service requirements. In this case, the UAV plays the role of a coordinator to provide high-quality communication service for GTs as well as maximize the benefit of caching. However, there exists an intractable issue that UAVs need to consider the optimization problem of multiple performance metrics with various types of optimization variables. To tackle the challenge, we propose a reinforcement learning-based approach to solve the multi-objective deployment problem while maintaining the optimal tradeoff between power consumption and backhaul saving. Numerical results evaluate the performance of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Abstract In this work we consider the problem of optimal cache placement in a D2D enabled cellular network. There are a number of helper devices in the area, which use their cached contents to help other users and offload traffic from the base station. The goal of cache placement is maximizing the offloaded traffic. We first formulate and optimally solve the cache placement problem as a mixed integer linear program. Then we propose a distributively implementable algorithm that clusters helpers. Helpers in each cluster collectively decide the contents to be cached, based on the content popularity. Numerical evaluations show that the proposed cache placement scheme always performs within 5% of the optimal result and it is robust to popularity profile and cache capacity. [ABSTRACT FROM AUTHOR]

Abstract Internet of Things (IoT) is composed of a large number of devices that are connected to the Internet and can exchange information regarding different applications including healthcare, transportation, and agriculture. In IoT, the information and communication technology refers to the involvement of computing to reduce the communication costs for information sharing along with managing the storage capabilities. It becomes more interesting and challenging by involving the concept of caching for optimization that can also be perfectly mapped to improve sensing capabilities. This paper presents the impact of Computing, Communication, and Caching (CCC) over the smart sensing capabilities to highlight the possible opportunities for this convergence in recent enabling technologies including 5G, cloud, fog and edge computing based networks. In this regard, different technologies have been identified that help solving bottlenecks during smart sensing operations by a large number of physical devices in IoT. We have investigated that how the convergence of CCC can improve the smart IoT sensing. A number of requirements for smart IoT based sensing are identified. Moreover, new challenges are identified that cause limited services for IoT applications due to sensing limitation of current and future convergence in IoT enabling technologies. [ABSTRACT FROM AUTHOR]

Abstract Offloading data traffic from Infrastructure-to-Device (I2D) to Device-to-Device (D2D) communications is a powerful tool for reducing congestion, energy consumption, and spectrum usage of mobile cellular networks. Prior network-level studies on D2D data offloading focus on high level performance metrics as the offloading efficiency , and take into account the radio propagation aspects by using simplistic wireless channel models. In this work, we consider a D2D data offloading protocol tailored to highly dynamic scenarios as vehicular environments, and evaluate its performance focusing on physical layer aspects, like energy consumption and spectral efficiency. In doing this, we take into account more realistic models of the wireless channel, with respect to the simplistic ones generally used in the previous studies. Our objective is twofold: first, to quantify the performance gain of the considered D2D offloading protocol with respect to a classic cellular network, based on I2D communications, in terms of energy consumption and spectral efficiency. Second, to show that using simplistic channel models may prevent to accurately evaluate the performance gain. Additionally, the use of more elaborated models allows to obtain insightful information on relevant system-level parameters settings, which would not be possible to obtain by using simple models. The considered channel models range from widely used models based on deterministic path loss formulas, to more accurate ones, which include effects like multipath fading and the associated frequency selectivity of wideband channels. These models have been proposed and validated, in the recent years, through large-scale measurements campaigns. Our results show that the considered protocol is able to achieve a reduction in the energy consumption of up to 35%, and an increase in the system spectral efficiency of 50%, with respect to the benchmark cellular system. The use of different channel models in evaluating these metrics may result, in the worst case, in a sixfold underestimation of the achieved improvement. [ABSTRACT FROM AUTHOR]

Ever since the advent of wireless communications, there has been a tremendous growth in data traffic and service demand. Both of the above quantities are expected to explosively dominate wireless communication networks, as we move on to the future 5G wireless communication systems. This paper involves the so-called hit probability related to data caching, a technique that mainly alleviates backbone network congestion and reduces latency, by storing frequently accessed data in mobile users' cache (mobility-aware caching) and leaves the least popular data for recovery from base stations. The hit probability is defined in the literature as the probability of specific file request by a user together with the successful delivery of the data packet to the user/network node that made the request. Considering three distributions, the uniform, the well-established Zipf-like distribution and the normal distribution, we allow a varying number of cached filles and observe the curves representing the hit probabilities and perform comparison. We provide interpretation of the related to optimality results i.e. greatest achievable hit probability. In a pico-cell of a cellular network of minimum radius of 50 m and a maximum radius of 200 m, we derive the transmission power level and verify that it complies to the typical transmission power of a pico-cell. A final remark involves the Compressed Sensing sparsity concept, where considering that the possibility that a file is cached with probability p, and not cached with probability 1 −  p , we examine the «sparsest» and «densest» scenario with respect to the number of cached files n opposed to the total N files in the aggregate users' cache, plotting the equivalent total probability. A final conclusion sets the issues of future work. [ABSTRACT FROM AUTHOR]

In this paper, we propose a cache replacement approach for Fog applications in Software Defined Networks (SDNs). Our approach depends on three functional factors in SDNs. These three factors are: age of data based on periodic request, popularity of on-demand requests, and the duration for which the sensor node is required to operate in active mode to capture the sensed readings. These factors are considered together to assign a value to the cached data in a software-defined network in order to retain the most valuable information in the cache for longer time. The higher the value, the longer the duration for which the data will be retained in the cache. This replacement strategy provides significant availability for the most valuable and difficult to sense data in the SDNs. Extensive simulations are performed to compare our approach against other dominant cache replacement policies under varying circumstances such as data popularity, cache size, network load, and connectivity degree. [ABSTRACT FROM AUTHOR]

Nowadays, as is envisioned as one of the most popular and challenging research areas due to the rapid growth of web data, information retrieval (IR) serves as a fundamental technology in large scale dataset processing and analyzing. IR systems usually involve handling massive and continuous retrieval requests in data matching, information filtering and other application scenarios. However, in the general applications of IR such as search engines, the individual response time is mostly emphasized and the efficiency of handling massive queries mainly relies on caching or similar technologies. For improving the overall efficiency of handling massive queries, we design a batched information retrieval system which first analyzes a batch of queries and then utilizes the repeats, similarity and correlations among queries to accelerate the retrievals. A concept-lattice-like structure called keyword-DAG (Directed Acyclic Graph) is first exploited to store and organize the similarity among queries. Accordingly a keyword-DAG processing algorithm namely pruning is devised to implement the batched retrieval. Then an incremental ranking algorithm is presented for the batched IR scenarios, which has be demonstrated (both in theory and practice) to be able to remarkably shorten the retrieval time. Finally, an overall planning algorithm is proposed for choosing the optimal pruning path and improving the utilization of memory. The experiment results show that our approach embraces far better performance compared with the traditional separate retrieval method in mass data processing and analyzing scenarios. [ABSTRACT FROM AUTHOR]

Hoarding or caching behaviour is a widely-used paradigm for examining a range of cognitive processes in birds, such as social cognition and spatial memory. However, much is still unknown about how caching develops in young birds, especially in the wild. Studying the ontogeny of caching in the wild will help researchers to identify the mechanisms that shape this advantageous foraging strategy. We examined the ontogeny of food caching behaviour in a wild New Zealand passerine, the North Island robin ( Petroica longipes ). For 12-weeks following fledging, we observed 34 juveniles to examine the development of caching and cache retrieval. Additionally, we compared the caching behaviour of juveniles at 12 weeks post-fledging to 35 adult robins to determine whether juveniles had developed adult-like caching behaviour by this age. Juveniles began caching mealworms shortly after achieving foraging independency. Multivariate analyses revealed that caching rate increased and handling time decreased with increasing age. Juveniles spontaneously began retrieving caches as soon as they had begun to cache and their retrieval rates then remained constant throughout their ensuing development. Likewise, the number of sites used by juveniles did not change with age. Juvenile sex, caregiver sex and the duration of post-fledging parental care did not influence the development of caching, cache retrieval, the number of cache sites used and the time juveniles spent handling mealworms. At 12 weeks post-fledging, juveniles demonstrated levels of caching, cache retrieval and cache site usage that were comparable to adults. However, juvenile prey handling time was still longer than adults. The spontaneous emergence of cache retrieval and the consistency in the number of cache sites used throughout development suggests that these aspects of caching in North Island robins are likely to be innate, but that age and experience have an important role in the development of adult caching behaviours. [ABSTRACT FROM AUTHOR]

For device-to-device (D2D) caching networks, we propose simple transmission strategies in order to minimize the outage probability and maximize the average. We first propose a blanket transmission scheme where multiple caching server devices (CSDs) simultaneously transmit the same content to a RD without any information exchange and signal processing at the CSDs. We also propose an opportunistic transmission scheme where we select a single CSD that has the largest channel gain from a request device (RD), and the selected CSD then transmits the requested content to RD. We derive the outage probabilities and average throughputs and we extend the results to the case of the D2D caching network in the presence of multiple RDs. We also analyze and compare the performances of the proposed transmission strategies according to the threshold rate and transmit signal-to-noise ratio (SNR). [ABSTRACT FROM AUTHOR]

The Information Centric Networking (ICN) approach proposes to rebuild the Internet communication model and to focus entirely on the data content. Although the Named Data Networking (NDN) architecture is considered as one of the most credible ICN architectures, it does not have an effective cache replacement system. Software Defined Networking (SDN) is an architecture where the control plan is completely decoupled from the data plane. In fact, with the steady growth of existing network infrastructures, we take advantage of the SDN to enhance the caching in the NDN architecture. In this paper, we introduce a Named Data Networking Cache replacement approach based on SDN, that we called NC-SDN. Thus, our proposal relies on data popularity calculation performed by the switches to define a cache replacement strategy. Through experimental tests, we evaluated the performance of our solution, and we compared it to the NDN equipped with different cache replacement policy. [ABSTRACT FROM AUTHOR]

To provide broadband access services to customers, which resides residential and enterprise field, WiMAX worldwide interoperability for microwave access is one of the famous wireless technology nowadays. In the real world, the number of users making the request for access content item are high. Therefore, by exploiting the features of an Information-centric network (ICN) such as caching capability of content routers, can be used to reduce the bandwidth consumption using centrality measures with network coding. In this way, a user can access the content item using their neighboring content routers rather than the server. Also, It requires scheduling algorithm in the MAC layer of its protocol stack for allocation of the bandwidth. Therefore, to avoid starvation, to maintain fairness and to provide high data speed among users with continuous service there is a need of scheduling algorithm in the uplink layer of the WiMAX. One of the widely used scheduling algorithms is the earliest deadline first (EDF) but it contains certain performance limitations. In this paper, we propose a Heuristic earliest deadline first (H-EDF) uplink scheduler in the MAC layer of the ICN-WiMAX such that it can efficiently schedule user’s request and provide a fairness in the ICN-WiMAX system. Further, we assess the performance of ICN-WiMAX using H-EDF scheme via simulations and provide a detailed analysis of its outcomes. [ABSTRACT FROM AUTHOR]

In this paper, we propose a Cognitive Caching approach for the Future Fog (CCFF) that takes into consideration the value of the exchanged data in Information Centric Sensor Networks (ICSNs). Our approach depends on four functional parameters in ICSNs. These four main parameters are: age of the data, popularity of on-demand requests, delay to receive the requested information and data fidelity. These parameters are considered together to assign a value to the cached data while retaining the most valuable one in the cache for prolonged time periods. This CCFF approach provides significant availability for most valuable and difficult to retrieve data in the ICSNs. Extensive simulations and case studies have been examined in this research in order to compare to other dominant cache management frameworks in the literature under varying circumstances such as data popularity, cache size, data publisher load, and node connectivity degree. Formal fidelity and trust analysis has been applied as well to emphasize the effectiveness of CCFF in Fog paradigms, where edge devices can retrieve unsecured data from the authorized nodes in the cloud. [ABSTRACT FROM AUTHOR]

The tremendous growth in the internet of things (IoT) technology has provided great support for e-healthcare applications. The remote health monitoring of patients at home is gaining popularity with the increase in design of number of IoT enabled wearable devices. The secure and efficient health data retrieval during continuous uploading of huge data on network is a challenge. In addition, another challenge exists due to limited resources available with IoT device to proceed efficient data retrieval. On the other hand, the edge cloud in edge computing technology provide abundant resources to its devices for various computations, storage and processing. The integration of IoT with edge would solve the resource constraint issue. However, efficient retrieval of health data from large pool of data would still be an issue due to IP based solutions offered by IoT. The Named Data Networking (NDN) is a promising solution for efficient delivery of data based on its name based content searching. This paper proposed NDN communication based secure remote healthcare monitoring framework by integrating IoT with edge computing where security to the each individual content is provided through hashing and encryption mechanism. The performance of the proposed framework is evaluated against its companion in Icarus simulator. The results proved the efficiency of our framework for content retrieval delay and cost associated in accessing the required data. [ABSTRACT FROM AUTHOR]

Worldwide Internet traffic has seen phenomenal growth in recent years. The main cause of this exponential upsurge is bandwidth-hungry video streaming and content-sharing services. Caching video files at the edge nodes is a prospective solution for faster content transmission and improved user experience. In addition, the transcoding of video contents is also crucial to address diverse user requirements. While the goal of unmanned aerial vehicle (UAV)-assisted systems so far is on computation offloading, the utilization of UAVs for caching and transcoding was not considered. In this paper, the proposed strategy introduces UAVs to serve requests for video files locally and alleviate backhaul pressure. The proposed optimization model reduces content transmission delay by exploiting caching and transcoding facilities at the UAVs. In addition to the optimization problem formulation, a low-complexity heuristic algorithm is introduced to find an acceptable solution in real time. Simulation results confirm that the proposed UAV-assisted model achieves significant performance gain by reducing content transmission delay and offloading backhaul traffic. [ABSTRACT FROM AUTHOR]

Data caching can remarkably improve the data availability in Mobile Ad Hoc Networks (MANETs) by reducing the access latency and bandwidth usage. Unfortunately, due to mobility and resource constraints, caching techniques designed for wired network are not applicable to MANETs. Moreover, frequent data updates, limited Mobile Terminal's (MT's) resources, insufficient wireless bandwidth and MT's mobility make cache management a tedious task. However, as MTs in MANETs may have similar tasks and share common interests, cooperative caching, which allows the sharing and coordination of cached data among multiple MTs, can be used to reduce the bandwidth and power consumption. Hence, a nearby MT can serve requests instead of the distant data source. The originality of this paper is concentrated on introducing an Adaptive Cooperative Caching Strategy (ACCS) with a novel cache replacement and prefetching policies. ACCS divides the network into non-overlapping clusters. Unlike other caching techniques that employ reactive routing protocols, ACCS employs a novel built-in table driven routing strategy with no additional penalties. Such behavior significantly minimizing the query delay. The secret lies in collecting the routing information during the clusters formulation, then fill the routing tables accordingly. ACCS has been compared against recent cooperative caching strategies. Experimental results have shown that ACCS outperforms other strategies as it introduced the maximum cache hit as well as the minimum query latency. [ABSTRACT FROM AUTHOR]

Software-Defined-Networking (SDN) and Content-Centric-Networking (CCN) are gathering an important consideration from academic world and manufacturing. They are perceived as a big opportunity for future Internet. In order to innovate and optimize network resources, the integration of CCN functionalities with OpenFlow architecture presents an attractive deal. However, there are deployment issues requiring a gradual approach to achieve these goals. The current specifications implementing CCN over OpenFlow have not been inspected sufficiently, although the conceptual design was investigated. This paper introduces OFAM-CCN, a new OpenFlow Architecture for Managing CCN to improve this process through new modifications based on Popularity Caching Strategy taking into account caching as a fundamental principle of CCN. [ABSTRACT FROM AUTHOR]

Meeting the performance expectation of web systems is a challenging task. Data grids, used as an additional tier in n-tier architecture of web applications, allow to speed up access to data. The key process in building of a data grid solution is the initial load, since the default methods of the initial load are very time consuming. Therefore, they have a big influence on lowering system availability. Authors propose a custom adapter that shorts the initial load time and, as a result, enlarges availability of a web system. Authors analysis the default initial load process and comparethe performance of default methods with the adapter developed by them. [ABSTRACT FROM AUTHOR]

Behaviour is an important mechanism for accommodating rapid environmental changes. Understanding a species’ capacity for behavioural plasticity is therefore a key, but understudied, aspect of developing tractable conservation and management plans under climate-change scenarios. Here, we quantified behavioural differences between American pikas ( Ochotona princeps ) living in an atypical, low-elevation habitat versus those living in a more-typical, alpine habitat. With respect to foraging strategy, low-elevation pikas spent more time consuming vegetation and less time caching food for winter, compared to high-elevation pikas. Low-elevation pikas were also far more likely to be detected in forested microhabitats off the talus than their high-elevation counterparts at midday. Finally, pikas living in the atypical habitat had smaller home range sizes compared to those in typical habitat or any previously published home ranges for this species. Our findings indicate that behavioural plasticity likely allows pikas to accommodate atypical conditions in this low-elevation habitat, and that they may rely on critical habitat factors such as suitable microclimate refugia to behaviourally thermoregulate. Together, these results suggest that behavioural adjustments are one important mechanism by which pikas can persist outside of their previously appreciated dietary and thermal niches. [ABSTRACT FROM AUTHOR]

We examined the caching behavior of the Clark’s nutcracker ( Nucifraga columbiana ), a relatively asocial corvid bird, during social and non-social conditions with conspecifics. Past work by Dally et al., (2004, 2005a) has found that the related but more social scrub jay ( Aphelocoma californica ) caches food in locations that are far away or that are more dimly illuminated when in the presence of an observer. Here, we used procedures comparable to those of Dally’s group to examine if the less social nutcracker is also sensitive to these same factors when caching in the presence of a conspecific. We found that nutcrackers cached nuts farther away, but showed no preference for caching in a dimly compared to a brightly illuminated area when in the presence of a conspecific observer. When comparing the measures of cache protection used in the past work with scrub jays the results are consistent with the social organization of these birds; that is, the less social nutcracker engaged in fewer cache protection behaviors than the more social scrub jays, However, we explore other possible explanations for our findings given the wider body of literature on corvid cache protection suggesting that nutcrackers and scrub jays may be more comparable. [ABSTRACT FROM AUTHOR]

Cellular service providers are under tremendous pressure to accommodate the burgeoning data needs of mobile subscribers. One intriguing solution is leveraging co-location, namely taking advantage of proximity between mobile devices for opportunistic collaboration. Co-location affords the usage of short range, low-power radio interfaces, avoiding expensive cellular interfaces in orthogonal device-to-device (D2D) channels. Taken one step further, could mobile devices exchange caches when in proximity, pre-staging popular content with one another? A first step to such research is understanding the potential with actual users. In this paper, we analyze our NetSense study of nearly two hundred smartphone users to explore the potential for pre-staging. We find that not only is the propagation velocity of data via co-location exchanges reasonable, the actual storage costs for pre-staging are also quite reasonable and within the normal free space of typical smartphone users. [ABSTRACT FROM AUTHOR]

Abstract: We investigate online browsing of interrelated content, represented as a catalog of items of interest featuring graph dependencies. The content is served to clients via a system of decentralized proxy caches connected to cloud servers. A client selects the next item to browse from the list of recommended items, displayed on the currently browsed item׳s catalog page. A cache has a limited size to have every item selected by its browsing clients available for local access. Thus, the system pays a penalty, whenever a client selects an item that cannot be served directly from the proxy. Conversely, the system gains a reward, if a client selects an immediately available item. We aim to select the items to cache that maximize the profit earned by the system, for the given cache capacity. We design two linear-time optimization techniques for finding the desired items to cache. We enhance the operation of the system via two additional strategies. The first one dynamically tracks the items׳ selection probabilities for a client, as a function of its prior catalog access pattern and those of its community peers. The second one constructs dynamic overlays, on behalf of the clients, that are used to share the selected items directly among them. This augments the system׳s serving capacity and enhances the clients׳ browsing experience. We study the performance of the optimization techniques via numerical experiments. They exhibit efficiency gains over reference methods, by exploiting the content dependencies and correlated community-driven access patterns of the clients. We also report proxy bandwidth savings achieved by our overlay strategy over state-of-the-art methods, on content access patterns of clients with Facebook or Twitter ties. [Copyright &y& Elsevier]

Highlights: [•] We ask whether scrub-jays prefer earlier cache-retrieval when caching. [•] Caching appears similar for trays that come back after 1h, 25h, and 49h. [•] Caching appears similar for delays of 7min and 26h when no choice of trays is provided. [•] We find no evidence of a preference to cache in trays that are more accessible for recovery. [ABSTRACT FROM AUTHOR]

Highlights: [•] Clark's nutcrackers cache in habitats with heavy snowfall and potential disturbance of local landmarks. [•] In captivity, Clark's nutcrackers were more accurate when recovering cached food in a small than in a large room. [•] Adding freestanding landmarks or a set of dividing panels did not markedly help nutcrackers to find their caches in the large room. [•] Nutcrackers seem to use structural features of rooms as important spatial cues. [Copyright &y& Elsevier]

Highlights: [•] The question of how tannin affects feeding and hoarding preferences of rodents still remains poorly understood. [•] We used artificial ‘seeds’ with different tannin levels to determine how tannin affects feeding and hoarding preferences. [•] Small rodents displayed a significant preference for low-tannin ‘seeds’ for both consumption and caching. [•] Tannin level was negatively correlated with the number of cached ‘seeds’ by rodents. [•] Our results did not support the high tannin hypothesis that acorns containing higher tannins are more likely to be cached. [ABSTRACT FROM AUTHOR]

Abstract: This paper describes a decision cache for the eXtensible Access Control Markup Language (XACML) that supports fine-grained authorisation and anonymisation of XML based messages and documents down to XML attribute and element level. The decision cache is implemented as an XACML obligation service, where a specification of the XML elements to be authorised and anonymised is sent to the Policy Enforcement Point (PEP) during initial authorisation. Further authorisation of individual XML elements according to the authorisation specification is then performed on all matching XML resources, and decisions are stored in the decision cache. This makes it possible to cache fine-grained XACML authorisation and anonymisation decisions, which reduces the authorisation load on the Policy Decision Point (PDP). The theoretical solution is related to a practical case study consisting of a privacy-enhanced intrusion detection system that needs to perform anonymisation of Intrusion Detection Message Exchange Format (IDMEF) XML messages before they are sent to a security operations centre that operates in privacy-preserving mode. The solution increases the scalability of XACML based authorisation significantly, and may be instrumental in implementing federated authorisation and anonymisation based on XACML in several areas, including intrusion detection systems, web services, content management systems and GRID based authentication and authorisation. [Copyright &y& Elsevier]

Abstract: Batch processing of raster data performed by geographic information systems (GIS) is a time consuming procedure. Modern high performance GPUs are able to perform hundreds of arithmetical operations in parallel. These GPUs can help to reduce the computing time of such operations. In addition, most of the commonly used raster operations are I/O-bounded. Memory transfer between hard disk and RAM takes up more time than computations. The scope of this paper is to present an efficient two-level caching strategy for raster data and an acceleration of selected raster operations using the GPU, which were implemented as a plugin for the open source software GRASS. An example data flow based on a real world use-case will be presented and the obtainable and practically expectable speedup will be measured and discussed. [Copyright &y& Elsevier]

Abstract: HTTP-based video streaming has been gaining popularity within the recent years. There are multiple benefits of relying on HTTP/TCP connections, such as the usage of the widely deployed network caches to relieve video servers from sending the same content to a high number of users and the avoidance of traversal issues with firewalls and NATs typical for RTP/UDP-based solutions. Therefore, many service providers resort to adopt HTTP streaming as the basis for their services. In this paper, the benefits of using the Scalable Video Coding (SVC) for a HTTP streaming service are shown, and the SVC based approach is compared to the AVC based approach. We show that network resources are more efficiently used and how the benefits of the traditional techniques can even be heightened by adopting the Scalable Video Coding (SVC) as the video codec for adaptive low delay streaming over HTTP. For the latter small playout-buffers are considered hence allowing low media access latency in the delivery chain and it is shown that adaptation is more effectively performed with the SVC based approach. [Copyright &y& Elsevier]

Abstract: In 1963, Niko Tinbergen suggested that to truly understand the behavior of an animal, the ultimate causes (e.g., adaptive value, evolutionary history) as well as the proximate mechanisms (e.g., neurobiology, development) that result in the production of the behavior must be understood in an integrated framework. We examine whether the study of spatial memory in food storing birds has adequately addressed Tinbergen''s questions and highlight the work of Sara Shettleworth, who has made a tremendous contribution to this area of study, and whom this issue honors. Our conclusion is that while the study of food caching and spatial memory in birds has been a very good model of a program of research that has addressed Tinbergen''s questions, additional work remains. [Copyright &y& Elsevier]

Abstract: This research is motivated by large-scale pervasive sensing applications. We examine the benefits and costs of caching data for such applications. We propose and evaluate several approaches to querying for, and then caching data in a sensor field data server. We show that for some application requirements (i.e., when delay drives data quality), policies that emulate cache hits by computing and returning approximate values for sensor data yield a simultaneous quality improvement and cost saving. This win–win is because when system delay is sufficiently important, the benefit to both query cost and data quality achieved by using approximate values outweighs the negative impact on quality due to the approximation. In contrast, when data accuracy drives quality, a linear trade-off between query cost and data quality emerges. We also identify caching and lookup policies for which the sensor field query rate is bounded when servicing an arbitrary workload of user queries. This upper bound is achieved by having multiple user queries share the cost of a single sensor field query. Finally, we demonstrate that our results are robust to the manner in which the environment being monitored changes using models for two different sensing systems. [Copyright &y& Elsevier]

Abstract: Delay-tolerant Networking (DTN) can enable ad-hoc communication within (sparse) mobile user communities and multi-hop Internet access where IP-based end-to-end communication would fail. DTN message forwarding in ad-hoc networks may lead to message replication and messages remaining stored on several nodes for some time. We leverage these characteristics and provide application support in intermediate nodes: we enable them to understand the resources contained in forwarded and locally stored DTN messages to perform application-specific processing. Based upon this, we create an opportunistic distributed storage for cooperative content caching and retrieval using the nodes’ buffers. [Copyright &y& Elsevier]

Abstract: Video-on-demand (VoD) is increasingly popular with internet users. However, VoD is costly due to the load placed on video servers. Peer-to-peer (P2P) techniques are an approach to alleviating server load through peer-assisted sharing. Existing studies on P2P VoD are mostly based on simulation and focus on areas such as overlay topology, but little is known about the effectiveness of P2P in a real VoD system. In this paper we present a comprehensive measurement study of GridCast, a deployed experimental P2P VoD system. Using a 2-month log of GridCast, we evaluate its scalability and end user experience. Motivated by the observations on user behavior and unused peer resource, we further optimize its performance. Our key findings are: (1) a moderate number of concurrent users can derive satisfactory user experience. However, good network bandwidth at peers and adequate server provisioning are still critical to good user experience; (2) a simple prefetching algorithm can be effective to improve random seeks; (3) a simple caching across multiple videos has great potential to further improve system scalability. Overall, we believe that it is feasible to provide a cost-effective P2P VoD service with acceptable user experience, and there is a fundamental tradeoff between good user experience and system scalability. [Copyright &y& Elsevier]

Abstract: Caching techniques can be used to reduce bandwidth consumption and data access delay in wireless ad hoc networks. When cache is used, the issue of cache consistency must be addressed, and maintaining strong cache consistency is desired in some strategic scenarios (e.g., battlefields). In these situations, the invalidation-based approach is preferred due to its low overhead. However, this approach may suffer from some security attacks. For example, malicious nodes (also called intruders) may drop, insert or modify invalidation messages to mislead receivers to use stale data or unnecessarily invalidate data that are still valid. In this paper, we first propose to employ the Invalidation Report (IR) based cache invalidation strategy to prevent intruders from dropping or modifying invalidation messages. Although digital signatures can be used to protect IRs, this has significantly high overhead in terms of computational and bandwidth overhead. To address this problem, we further propose a family of randomized grouping-based schemes for intrusion detection, damage recovery and intruder identification. Extensive analysis and simulations are performed to evaluate the proposed schemes. The results show that our solution can achieve a satisfactory level of security with low overhead. [Copyright &y& Elsevier]

Abstract: In the Internet, proxy servers play the key roles between users and web sites, which could reduce the response time of user requests and save network bandwidth. Basically, an efficient buffer manager should be built in a proxy server to cache frequently accessed documents in the buffer, thereby achieving better response time. In the paper, we developed an access sequence miner to mine popular surfing 2-sequences with their conditional probabilities from the proxy log, and stored them in the rule table. Then, according to buffer contents and the rule table, a prediction-based buffer manager also developed here will make appropriate actions such as document caching, document prefetching, and even cache/prefetch buffer size adjusting to achieve better buffer utilization. Through the simulation, we found that our approach has much better performance than the other ones, in the quantitative measures such as hit ratios and byte hit ratios of accessed documents. [Copyright &y& Elsevier]

Abstract: The rapid development of networking technologies has made it possible to construct a distributed database that involves a huge number of sites. Query processing in such a large-scaled system poses serious challenges beyond the scope of traditional distributed algorithms. In this paper, we propose a new algorithm BRANCA for performing top-k retrieval in these environments. Integrating two orthogonal methodologies “semantic caching” and “routing indexes”, BRANCA is able to solve a query by accessing only a small number of servers. Our algorithmic findings are accompanied with a solid theoretical analysis, which rigorously proves the effectiveness of BRANCA. Extensive experiments verify that our technique outperforms the existing methods significantly. [Copyright &y& Elsevier]

A materialized view or Materialized Query Table (MQT) is an auxiliary table with precomputed data that can be used to significantly improve the performance of a database query. A Materialized Query Table Advisor (MQTA) is often used to recommend and create MQTs. The state-of-the-art MQTA works in a standalone database server where MQTs are placed on the same server as that in which the base tables are located. The MQTA does not apply to a federated or scaleout scenario in which MQTs need to be placed on other servers close to applications (i.e. a frontend database server) for offloading the workload on the backend database server. In this paper, we propose a Data Placement Advisor (DPA) and load balancing strategies for multi-tiered database systems. Built on top of the MQTA, DPA recommends MQTs and advises placement strategies for minimizing the response time for a query workload. To demonstrate the benefit of the data placement advising, we implemented a prototype of DPA that works with the MQTA in the IBM® DB2® Universal Database™ (DB2 UDB) and the IBM WebSphere® Information Integrator (WebSphere II). The evaluation results showed substantial improvements of workload response times when MQTs are intelligently recommended and placed on a frontend database server subject to space and load characteristics for TPC-H and OLAP type workloads. [Copyright &y& Elsevier]

Abstract: The impaling of prey is a behavioral trait restricted to the true shrikes (Laniidae). Here, we suggest the ontogeny of this behavior. We believe impaling originated from wedging behavior that occurs among several other groups of birds, including corvids. Accidental impaling during wedging was likely the behavioral precursor of purposeful impaling. Fidelity to impaling sites lead to the creation of caches, which were eventually used by females for male evaluation. Caching allowed males to increase their fitness by using the caches as a display to attract potential mates. Further, caching is used by shrikes to demarcate territories, store food for inclement weather or periods of stress in the breeding cycle, divide labor between the breeding pair, and for “aging” while deterrent chemicals in prey decompose. [Copyright &y& Elsevier]

This paper is concerned with online caching algorithms for the (n,k)-companion cache, defined by Brehob et al. (J. Scheduling 6 (2003) 149). In this model the cache is composed of two components: a k-way set-associative cache and a companion fully associative cache of size n. We show that the deterministic competitive ratio for this problem is (n+1)(k+1)-1, and the randomized competitive ratio is O(log n log k) and Ω(log n+log k). [Copyright &y& Elsevier]

We study the online page replication problem. We present a new randomized online algorithm for rings which is 2.37297-competitive, improving the best previous result of 3.16396. We also show that no randomized online algorithm is better than 1.75037-competitive on the ring; previously, only a 1.58198 bound for a single edge was known. We extend the problem in several new directions: continuous metrics, variable size requests, and replication before service. This yields simplified proofs of several known results. [Copyright &y& Elsevier]

Traditionally, optimal foraging theory has been applied to situations in which a forager makes decisions about current resource consumption based on tradeoffs in resource attributes (e.g. caloric intake versus handling time). Food storage, which permits animals to manage the availability of food in space and time, adds a complex dimension to foraging decisions, and may influence the predictions of traditional foraging theory. One key question about the role of caching behavior in optimal foraging theory is the degree to which information about future value might influence foraging decisions. To investigate this question, we use a simple prey selection model that minimizes the time spent foraging and is modified to include food storage and changes in nutritional value through time. We used simulations to evaluate time spent in foraging activities per prey item and optimal foraging strategies (e.g. cache versus consume immediately) for 3125 parameter combinations, representing different abundance levels, handling times, and nutritional values. Using discriminant function analysis it was possible to distinguish situations where “caching” versus “immediate consumption” were optimal strategies with abundance as the single predictive variable. The circumstances where caching was optimal were characterized by a decline in prey abundance and an increase in nutritional value through time. These results provide a framework for identifying subtle differences in foraging behavior when future value is accounted for thereby improving our predictive understanding of how caching animals forage. [Copyright &y& Elsevier]

Reducing initial delay of playing time, delay jitter during playing time, and network bandwidth utilization is important for IP-based multimedia streaming services. In heterogeneous computing environments, diversity of computing power and network connection of different devices makes a stable quality of streaming service more difficult. In order to achieve these goals, our quality of service (QoS)-aware middleware for collaborative multimedia streaming and caching service exploits the proximity of a set of peer clients and temporal and spatial locality of cached media streams on these clients. Peer clients collaborate together to deliver streams to heterogeneous client(s) with QoS guarantees. Our paper shows collaborative techniques for multimedia streaming, scheduling and pre-fetching embedded in the QoS middleware architecture for dynamic group management of heterogeneous computing devices. In addition, we provide an underlying QoS-provisioning mechanism to support not only heterogeneous clients, but also dynamic configuration change of them. [Copyright &y& Elsevier]

A software RAID file system is defined as a system that distributes data redundantly across an array of disks attached to each of the workstations connected on a high-speed network. This configuration provides higher throughput and availability compared to conventional file systems. In this paper, we consider two specific issues regarding the distribution of data among the cluster, namely, striping and buffer caching for such an environment. Through simulation studies we compare the performance of various striping methods and show that for effective striping in software RAID file systems, it must take advantage of its flexible nature. Further, for buffer caching, we show that conventional caching schemes developed for distributed systems are insufficient, and that the Exclusively Old Data and Parity scheme that is presented in this paper, overcomes the limitations of the previously proposed schemes. [Copyright &y& Elsevier]

• Providing efficient routing and content management for ICN. • It enables bandwidth and cost-based routing for mobile and social sensing applications. • Caching is an important feature of ICN. • Cache replacement policy proposed to improve ICN performance. Information-Centric Network (ICN) is an essential networking model which contains several future Internet research activities. This paper considers ICN architecture for mobile and social sensing data. Routing and caching are among the most critical features of ICN, which improves the performance of efficiency of network and content sharing by fulfilling user requirements with cached content. This paper introduces a new routing model for information-centric network based on least bandwidth and cost (LBC) with two cache replacement policies. The cache replacement policies find and replace the content in the free cache space. Time aware Least Recently Used (TLRU) and Least Frequent Recently Used (LFRU) are employed as a cache replacement policy. The proposed algorithm implemented and compared, with the previous algorithm in terms of the following metrics success rate, hop count and delay. The results of the experiments show that the proposed algorithm is more effective compared to other algorithms. [Display omitted] [ABSTRACT FROM AUTHOR]

Cloud radio access network (Cloud-RAN) has been considered as a potential candidate for the next generation of radio access networks. It addresses many challenges in terms of flexibility, scalability, radio resource management and energy efficiency. Caching popular contents at radio remote heads (RRHs) plays an important role for reducing fronthaul traffic congestion and delay in cache-enabled Cloud-RAN. Although, mathematical optimization methods have shown to be providing numerical solutions for addressing key signal processing issues in Cloud-RAN, the exponential complexity hinders their application in practice, particularly in large networks. Learning-based methods have become attractive to overcome the complexity issues associated with the mathematical optimization methods. Several subset selection problems have been formulated as a mixed-integer non linear program (MINLP) in wireless networks. Determinantal point process (DPP) is a probabilistic model of choosing two similar items which are negatively correlated. In this paper, we propose a DPP based-learning (DPPL) framework to obtain a subset of admitted users for cache-enabled Cloud-RAN with limited fronthaul capacity. The formulated problem of minimizing the total network cost including power and fronthaul cost while admitting as many users as possible is converted into mixed-integer second order cone programming (MI-SOCP). The subset of admitted users is obtained by learning the quality-diversity trade-off of the DPP using the optimal subsets of admitted users which are obtained by the optimization approach. We then propose an optimization algorithm to determine the beamforming and the base station-user allocation for the obtained subset of admitted users. We provide numerical results to assess the performance and complexity of the proposed DPPL algorithm and compare it with its optimization counterpart. The results reveal that the proposed DPPL can achieve a comparable performance with much lower complexity. [ABSTRACT FROM AUTHOR]