Smart-routers develop greatly in recent years as one of the representative products of IoT and Smart home. Different from traditional routers, they have storage and processing capacity. Actually, smart-routers in the same location or ISP have better link conditions and can provide high quality service to each other. Therefore, for the content required services, how to construct the overlay network and efficiently deploy replications of popular content in smart-routers' network are critical. The performance of existing centralized models is limited by the bottleneck of the single point's performance. In order to improve the stability and scalability of the system through the capability of smart-router, we propose a novel intelligent and decentralized content diffusion system in smart-router network. In the system, the content will be quickly and autonomously diffused in the network which follows the specific requirement of coverage rate in neighbors. Furthermore, we design a heuristic node selection algorithm (MIG) and a replacement algorithm (MCL) to assist the diffusion of content. Specifically, system based MIG will select neighbor with the maximum value of information gain to cache the replication. The replication with the least loss of the coverage rate gain will be replaced in the system based on MCL. Through the simulation experiments, at the same requirement of coverage rate, MIG can reduce the number of replications by at least 20.2% compared with other algorithms. Compared with other replacement algorithms, MCL achieves the best successful service rate which means how much ratio of the service can be provided by neighbors. The system based on the MIG and MCL can provide stable service with the lowest bandwidth and storage cost.

In content oriented networks (CON), routers in a network are generally equipped with local cache storages and store incoming contents temporarily. Efficient utilization of total cache storage in networks is one of the most important technical issues in CON, as it can reduce content server load, content download latency and network traffic. Performance of networked cache is reported to strongly depend on both cache decision and content request routing. In this paper, we evaluate several combinations of these two strategies. Especially for routing, we take up off-path cache routing, Breadcrumbs, as one of the content request routing proposals. Our performance evaluation results show that off-path cache routing, Breadcrumbs, suffers low performance with cache decisions which generally has high performance with shortest path routing (SPR), and obtains excellent performance with TERC (Transparent En-Route Cache) which is well-known to have low performance with widely used SPR. Our detailed evaluation results in two network environments, emerging CONs and conventional IP, show these insights hold in both of these two network environments.

Saliency quality assessment aims at estimating the objective quality of a saliency map without access to the ground-truth. Existing works typically evaluate saliency quality by utilizing information from saliency maps to assess its compactness and closedness while ignoring the information from image content which can be used to assess the consistence and completeness of foreground. In this letter, we propose a novel multi-information fusion network to capture the information from both the saliency map and image content. The key idea is to introduce a siamese module to collect information from foreground and background, aiming to assess the consistence and completeness of foreground and the difference between foreground and background. Experiments demonstrate that by incorporating image content information, the performance of the proposed method is significantly boosted. Furthermore, we validate our method on two applications: saliency detection and segmentation. Our method is utilized to choose optimal saliency map from a set of candidate saliency maps, and the selected saliency map is feeded into an segmentation algorithm to generate a segmentation map. Experimental results verify the effectiveness of our method.

If a shared IP network is to deliver large-volume streaming media content, such as real-time videos, we need a technique for explicitly setting and dynamically changing the transmission paths used to respond to the congestion situation of the network, including multi-path transmission of a single-flow, to maximize network bandwidth utilization and stabilize transmission quality. However, current technologies cannot realize flexible multi-path transmission because they require complicated algorithms for route searching and the control load for route changing is excessive. This paper proposes a scheme that realizes routing control for multi-path transmission by combining multiple virtual networks on the same physical network. The proposed scheme lowers the control load incurred in creating a detour route because routing control is performed by combining existing routing planes. In addition, our scheme simplifies route searching procedure because congestion avoidance control of multi-path transmission can be realized by the control of a single path. An experiment on the JGN-X network virtualization platform finds that while the time taken to build an inter-slice link must be improved, the time required to inspect whether each slice has virtual nodes that can be connected to the original slice and be used as a detour destination can be as short as 40 microseconds per slice even with large slices having more than 100 virtual nodes.

In-network guidance to off-path cache, Breadcrumbs, has been proposed for cache network. It guides content requests to off-path cached contents by using the latest content download direction pointer, breadcrumbs. In Breadcrumbs, breadcrumb pointer is overwritten when a new content download of the corresponding content passes through a router. There is a possibility that slightly old guidance information for popular contents might lead to better cached content than the latest one. In this paper, we propose a new in-network guidance, Multiple-Breadcrumbs, which holds old breadcrumbs even with the latest breadcrumb pointer generated with a new content download. We focus on its content search capability and propose Throughput Sensitive selection that selects the content source giving the best estimated throughput. Our performance evaluation gives interesting results that our proposed Multiple Breadcrumbs with Throughput Sensitive selection improves not only throughput for popular contents but also for unpopular contents.

Information-centric networking (ICN) has gained attention from network research communities due to its capability of efficient content dissemination. In-network caching function in ICN plays an important role to achieve the design motivation. However, many researchers on in-network caching due to its ability to efficiently disseminate content. The in-network caching function in ICN plays an important role in realizing the design goals. However, many in-network caching researchers have focused on where to cache rather than how to cache: the former is known as content deployment in the network and the latter is known as cache replacement in an ICN router. Although the cache replacement has been intensively researched in the context of web-caching and content delivery network previously, networks, the conventional approaches cannot be directly applied to ICN due to the fine granularity of chunks in ICN, which eventually changes the access patterns. In this paper, we argue that ICN requires a novel cache replacement algorithm to fulfill the requirements in the design of a high performance ICN router. Then, we propose a novel cache replacement algorithm to satisfy the requirements named Compact CLOCK with Adaptive Replacement (Compact CAR), which can reduce the consumption of cache memory to one-tenth compared to conventional approaches. In this paper, we argue that ICN requires a novel cache replacement algorithm to fulfill the requirements set for high performance ICN routers. Our solution, Compact CLOCK with Adaptive Replacement (Compact CAR), is a novel cache replacement algorithm that satisfies the requirements. The evaluation result shows that the consumption of cache memory required to achieve a desired performance can be reduced by 90% compared to conventional approaches such as FIFO and CLOCK.

Creating new content based on existing original work is becoming popular especially among amateur creators. Such new content is called derivative work and can be transformed into the next new derivative work. Such derivative work creation is called “N-th order derivative creation.” Although derivative creation is popular, the reason an individual derivative work was created is not observable. To infer the factors that trigger derivative work creation, we have proposed a model that incorporates three factors: (1) original work's attractiveness, (2) original work's popularity, and (3) derivative work's popularity. Based on this model, in this paper, we describe a public web service for browsing derivation factors called Songrium Derivation Factor Analysis. Our service is implemented by applying our model to original works and derivative works uploaded to a video sharing service. Songrium Derivation Factor Analysis provides various visualization functions: Original Works Map, Derivation Tree, Popularity Influence Transition Graph, Creator Distribution Map, and Creator Profile. By displaying such information when users browse and watch videos, we aim to enable them to find new content and understand the N-th order derivative creation activity at a deeper level.

IEEE 802.11ah is a new wireless standard for large-scale wireless connectivity in IoT and M2M applications. One of the major requirements placed on IEEE 802.11ah is the energy-efficient communication of several thousand stations with a single access point. This is especially difficult to achieve during network initialization, because the several thousand stations must rely on the rudimentary approach of random channel access, and the inevitable increase in channel access contention yields a long association delay. IEEE 802.11ah has introduced an authentication control mechanism that classifies stations into groups, and only a small number of stations in a group are allowed to access the medium at a time. Although the grouping strategy provides fair channel access to a large number of stations, the presence of several thousand stations and limitation that only a group can use the channel at a time, causes the association time to remain excessive. In this paper, we propose a novel block association method that enables simultaneous association of all groups. Our experiments verify that our block association method decreases the total association time by many folds.

In this paper, we use the MCA (Multi-Cache Approximation) algorithm to numerically determine cache hit probability in a multi-cache network. We then analytically obtain performance metrics for Content-Centric networking (CCN). Our analytical model contains multiple routers, multiple repositories (e.g., storage servers), and multiple entities (e.g., clients). We obtain three performance metrics: content delivery delay (i.e., the average time required for an entity to retrieve a content through a neighboring router), throughput (i.e., number of contents delivered from an entity per unit of time), and availability (i.e., probability that an entity can successfully retrieve a content from a network). Through several numerical examples, we investigate how network topology affects the performance of CCN. A notable finding is that content caching becomes more beneficial in terms of content delivery time and availability (resp., throughput) as distance between the entity and the requesting repository narrows (resp., widens).

Information-centric networking (ICN) has received increasing attention from all over the world. The novel aspects of ICN (e.g., the combination of caching, multicasting, and aggregating requests) is based on names that act as addresses for content. The communication with name has the potential to cope with the growing and complicating Internet technology, for example, Internet of Things, cloud computing, and a smart society. To realize ICN, router hardware must implement an innovative cache replacement algorithm that offers performance far superior to a simple policy-based algorithm while still operating with feasible computational and memory overhead. However, most previous studies on cache replacement policies in ICN have proposed policies that are too blunt to achieve significant performance improvement, such as first-in first-out (popularly, FIFO) and random policies, or impractical policies in a resource-restricted environment, such as least recently used (LRU). Thus, we propose CLOCK-Pro Using Switching Hash-tables (CUSH) as the suitable policy for network caching. CUSH can identify and keep popular content worth caching in a network environment. CUSH also employs CLOCK and hash-tables, which are low-overhead data structure, to satisfy the cost requirement. We numerically evaluate our proposed approach, showing that our proposal can achieve cache hits against the traffic traces that simple conventional algorithms hardly cause any hits.

Cooperative caching is a key technique to reduce rapid growing video-on-demand's traffic by aggregating multiple cache storages. Existing strategies periodically calculate a sub-optimal allocation of the content caches in the network. Although such technique could reduce the generated traffic between servers, it comes with the cost of a large computational overhead. This overhead will be the cause of preventing these caches from following the rapid change in the access pattern. In this paper, we propose a light-weight scheme for cooperative caching by grouping contents and servers with color tags. In our proposal, we associate servers and caches through a color tag, with the aim to increase the effective cache capacity by storing different contents among servers. In addition to the color tags, we propose a novel hybrid caching scheme that divides its storage area into colored LFU (Least Frequently Used) and no-color LRU (Least Recently Used) areas. The colored LFU area stores color-matching contents to increase cache hit rate and no-color LRU area follows rapid changes in access patterns by storing popular contents regardless of their tags. On the top of the proposed architecture, we also present a new routing algorithm that takes benefit of the color tags information to reduce the traffic by fetching cached contents from the nearest server. Evaluation results, using a backbone network topology, showed that our color-tag based caching scheme could achieve a performance close to the sub-optimal one obtained with a genetic algorithm calculation, with only a few seconds of computational overhead. Furthermore, the proposed hybrid caching could limit the degradation of hit rate from 13.9% in conventional non-colored LFU, to only 2.3%, which proves the capability of our scheme to follow rapid insertions of new popular contents. Finally, the color-based routing scheme could reduce the traffic by up to 31.9% when compared with the shortest-path routing.

Community detection is an important task in the social network analysis field. Many detection methods have been developed; however, they provide little semantic interpretation for the discovered communities. We develop a framework based on joint matrix factorization to integrate network topology and node content information, such that the communities and their semantic labels are derived simultaneously. Moreover, to improve the detection accuracy, we attempt to make the community relationships derived from two types of information consistent. Experimental results on real-world networks show the superior performance of the proposed method and demonstrate its ability to semantically annotate communities.

We propose a novel method, built upon the hierarchical Dirichlet process hidden semi-Markov model, to reveal the content structures of unstructured domain-specific texts. The content structures of texts consisting of sequential local contexts are useful for tasks, such as text retrieval, classification, and text mining. The prominent feature of our model is the use of the recursive uniform partitioning, a stochastic process taking a view different from existing HSMMs in modeling state duration. We show that the recursive uniform partitioning plays an important role in avoiding the rapid switching between hidden states. Remarkably, our method greatly outperforms others in terms of ranking performance in our text retrieval experiments, and provides more accurate features for SVM to achieve higher F1 scores in our text classification experiments. These experiment results suggest that our method can yield improved representations of domain-specific texts. Furthermore, we present a method of automatically discovering the local contexts that serve to account for why a text is classified as a positive instance, in the supervised learning settings.

IEEE 802.11ah is an emerging wireless LAN standard in the sub-1-GHz license-exempt bands for cost-effective and range-extended communication. One of the most challenging issues that need to be overcome in relation to IEEE 802.11ah is to ensure that thousands of stations are able to associate efficiently with a single access point. During network initialization, several thousand stations try to associate with the access point, leading to heavy channel contention and long association delay. Therefore, IEEE 802.11ah has introduced an authentication control mechanism that classifies stations into groups and only a small number of stations in a group are allowed to access the medium in a beacon interval. This grouping strategy provides fair channel access to a large number of stations. However, the approach to grouping the stations and determining the best group size is undefined in the draft of IEEE 802.11ah. In this paper, we first model the authentication/association in IEEE 802.11ah. Our analysis shows that there exists the best group size that results in minimal association delay. Consequently, the analytical model is extended to determine the best group size. Finally, an enhanced authentication control algorithm, which utilizes the best group size to provide the minimum association delay, is proposed. The numerical and the simulation results we obtained with the proposed method demonstrate that our method succeeds in minimizing the association delay.

Index generation functions model content-addressable memory, and are useful in virus detectors and routers. Linear decompositions yield simpler circuits that realize index generation functions. This paper proposes a balanced decision tree based heuristic to efficiently design linear decompositions for index generation functions. The proposed heuristic finds a good linear decomposition of an index generation function by using appropriate cost functions and a constraint to construct a balanced tree. Since the proposed heuristic is fast and requires a small amount of memory, it is applicable even to large index generation functions that cannot be solved in a reasonable time by existing heuristics. This paper shows time and space complexities of the proposed heuristic, and experimental results using some large examples to show its efficiency.

This paper presents a method to realize index generation functions using multiple Index Generation Units (IGUs). The architecture implements index generation functions more efficiently than a single IGU when the number of registered vectors is very large. This paper proves that independent linear transformations are necessary in IGUs for efficient realization. Experimental results confirm this statement. Finally, it shows a fast update method to IGUs.

This paper illustrates various content sharing systems that take advantage of cloud's storage and computational resources as well as their supporting conventional technologies. First, basic technology concepts supporting cloud-based systems from a client-server to cloud computing as well as their relationships and functional linkages are shown. Second, the taxonomy of cloud-based system models from the aspect of multiple clouds' interoperability is explained. Interoperability can be categorized into provider-centric and client-centric scenarios. Each can be further divided into federated clouds, hybrid clouds, multi-clouds and aggregated service by broker. Third, practical cloud-based systems related to contents sharing are reported and their characteristics are discussed. Finally, future direction of cloud-based content sharing is suggested.

Conventional image retargeting methods fail to avoid distortion in the case where visually important regions are distributed all over the image. To reduce distortions, this paper proposes a novel image retargeting method that incorporates letterboxing into an image warping framework. Letterboxing has the advantage of producing results without distortion or content loss although being unable to use the entire display area. Therefore, it is preferable to combine a retargeting method with a letterboxing operator when displaying images in full screen. Experimental results show that the proposed method is superior to conventional methods in terms of visual quality measured by an objective metric.

The quality assessment of screen content images (SCIs) has been attractive recently. Different from natural images, SCI is usually a mixture of picture and text. Traditional quality metrics are mainly designed for natural images, which do not fit well into the SCIs. Motivated by this, this letter presents a simple and effective method to naturalize SCIs, so that the traditional quality models can be applied for SCI quality prediction. Specifically, bicubic interpolation-based up-sampling is proposed to achieve this goal. Extensive experiments and comparisons demonstrate the effectiveness of the proposed method.

In the present paper, we propose a broadcast ARQ protocol based on the concept of index coding. In the proposed scenario, a server wishes to transmit a finite sequence of packets to multiple receivers via a broadcast channel with packet erasures until all of the receivers successfully receive all of the packets. In the retransmission phase, the server produces a coded packet as a retransmitted packet based on the side-information sent from the receivers via feedback channels. A notable feature of the proposed protocol is that the decoding process at the receiver side has low decoding complexity because only a small number of addition operations are needed in order to recover an intended packet. This feature may be preferable for reducing the power consumption of receivers. The throughput performance of the proposed protocol is close to that of the ideal FEC throughput performance when the erasure probability is less than 0.1. This implies that the proposed protocol provides almost optimal throughput performance in such a regime.