In recent 3GPP (3rd Generation Partnership Project) standardization meetings, D2D (Device-to-Device) discovery has been a major issue to support commercial/social services and public safety in disaster environment, and TDM (Time Division Multiplexing) based discovery channel structure is mainly considered to prevent mutual interference between D2D and cellular traffic. In this structure, D2D discovery among the same cell UEs (User Equipment) has no problem because they have the same timing source. However, LTE (Long Term Evolution) assumes an asynchronous network where two adjacent eNBs (evolved Node B) have a symbol-level timing offset. For that reason, asynchronous interference among discovery signals can appear in inter-cell D2D discovery. Therefore, channel re-use scheduling was studied previously in which neighboring cells do not use the same portion of the extended discovery channel and other non-neighboring cells re-use it. However, it still shows interference problems in small cell networks which cause substantial cellular traffic loss. Therefore, in this paper, we propose a novel discovery channel scheduling in which eNBs time-align their discovery channels from each other by sample-level. In the proposed scheme, serving eNB requests cell edge UEs to estimate NTD (Network Time Difference) between serving eNB and neighboring eNB. Then, considering multiple NTDs, eNB adjusts the sample position of its discovery channel based on a novel decision rule. We verify that the proposed scheme can match the discovery performance of a synchronous network with less cellular uplink loss.

We have already proposed a service discovery scheme using mobile agents for mobile ad hoc networks where node positions in the network and the network topology change frequently. Mobile agents autonomously migrate among nodes and then perform a given task at a node. In the service discovery scheme using mobile agents, mobile agents collect and disseminate services in the network so it is most important how the mobile agents migrate in the network. Therefore, we propose two types of mobile agent migration mechanisms in this paper. One is that mobile agents migrate to the nodes at which other mobile agents do not stay, the other is that mobile agents migrate to the nodes to which mobile agents can disseminate a lot of service information. Finally, we conducted simulation experiments to investigate the performance of the proposed migration mechanisms with respect to the service dissemination time and rate.

By the motivation to discover patterns in massive structured data in the form of graphs and trees, we study a special case of the k-subtree enumeration problem with a tree of n nodes as an input graph, which is originally introduced by (Ferreira, Grossi, and Rizzi, ESA'11, 275-286, 2011) for general graphs. Based on reverse search technique (Avis and Fukuda, Discrete Appl. Math., vol.65, pp.21-46, 1996), we present the first constant delay enumeration algorithm that lists all k-subtrees of an input rooted tree in O(1) worst-case time per subtree. This result improves on the straightforward application of Ferreira et al.'s algorithm with O(k) amortized time per subtree when an input is restricted to tree. Finally, we discuss an application of our algorithm to a modification of the graph motif problem for trees.

To facilitate the discovery of mobile apps in personal devices, we present the personalized live homescreen system. The system mines the usage patterns of mobile apps, generates personalized predictions, and then makes apps available at users' hands whenever they want them. Evaluations have verified the promising effectiveness of our system.

Resource discovery is an essential function for distributed mobile applications integrated in vehicular communication systems. Key requirements of the mobile resource discovery are wide-area geographic-based discovery and scalable resource discovery not only inside a vehicular ad-hoc network but also through the Internet. While a number of resource discovery solutions have been proposed, most of them have focused on specific scale of network. Furthermore, managing a large number of mobile resources in the Internet raises a scalability issue due to the mobility of vehicles. In this paper, we design a solution to wide area geographical mobile resource discovery in heterogeneous networks composed of numerous mobile networks possibly connected to the Internet. The proposed system relies on a hierarchical publish-subscribe architecture and geographic routing so that users can locate resources according to geographical coordinates without scalability issue. Furthermore we propose a location management mechanism for mobile resources, which enables to reduce periodic updates of geographical location. Numerical analysis and simulation results show that our system can discover mobile resources without overloading both mobile network and the Internet.

This paper proposes a device discovery method for consolidated IP and ZigBee home networks. The method broadcasts an IP multicasted device discovery request of UPnP, m-search, in the ZigBee network as a Constrained Application Protocol (CoAP) message. Upon receiving the m-search broadcast, ZigBee devices respond after a constant time delay with their device description Universal Resource Name (URN). We refer to this device discovery mechanism as transparent msearch. Transparent m-search enables reliable and swift device discovery in home networks which may include constrained networks such as ZigBee. It is revealed by an experiment with 41 ZigBee devices that the delayed response from ZigBee devices is essential to avoid collisions between m-search broadcast and responses from devices and, as a result, to secure the reliability of device discovery. Since the transparent m-search requires the receiving ZigBee devices to respond with their device description URNs, the execution time of device discovery is significantly improved. In our experiment with 41 ZigBee devices, a conventional m-search took 38.1 second to complete device discovery while that of transparent m-search took only 6.3 second.

A scalable pattern discovery by compression is proposed. A string is representable by a context-free grammar deriving the string deterministically. In this framework of grammar-based compression, the aim of the algorithm is to output as small a grammar as possible. Beyond that, the optimization problem is approximately solvable. In such approximation algorithms, the compressor based on edit-sensitive parsing (ESP) is especially suitable for detecting maximal common substrings as well as long frequent substrings. Based on ESP, we design a linear time algorithm to find all frequent patterns in a string approximately and prove several lower bounds to guarantee the length of extracted patterns. We also examine the performance of our algorithm by experiments in biological sequences and other compressible real world texts. Compared to other practical algorithms, our algorithm is faster and more scalable with large and repetitive strings.

Recently, numerous service discovery protocols have been introduced in the open literature. Unfortunately, many of them did not consider security issues, and for those that did, many security and privacy problems still remain. One important issue is to protect the privacy of a service provider while enabling an end-user to search an alternative service using multiple keywords. To deal with this issue, the existing protocols assumed that a directory server should be trusted or owned by each service provider. However, an adversary may compromise the directory server due to its openness property. In this paper, we suggest an efficient verification of service subscribers to resolve this issue and analyze its performance and security. Using this method, we propose an efficient and secure service discovery protocol protecting the privacy of a service provider while providing multiple keywords search to an end-user. Also, we provide performance and security analysis of our protocol.

We present a scalable approach to automatically discovering particular objects (as opposed to object categories) from a set of images. The basic idea is to search for local image features that consistently appear in the same images under the assumption that such co-occurring features underlie the same object. We first represent each image in the set as a set of visual words (vector quantized local image features) and construct an inverted file to memorize the set of images in which each visual word appears. Then, our object discovery method proceeds by searching the inverted file and extracting visual word sets whose elements tend to appear in the same images; such visual word sets are called co-occurring word sets. Because of unstable and polysemous visual words, a co-occurring word set typically represents only a part of an object. We observe that co-occurring word sets associated with the same object often share many visual words with one another. Hence, to obtain the object models, we further cluster highly overlapping co-occurring word sets in an agglomerative manner. Remarkably, we accelerate both extraction and clustering of co-occurring word sets by Min-Hashing. We show that the models generated by our method can effectively discriminate particular objects. We demonstrate our method on the Oxford buildings dataset. In a quantitative evaluation using a set of ground truth landmarks, our method achieved higher scores than the state-of-the-art methods.

Energy conservation is an important issue in mobile ad hoc networks (MANET), where the terminals are always supplied with limited energy. A new routing protocol is presented according to the study on the influence of low-energy nodes in ad hoc networks. The novel routing protocol (energy sensing routing protocol, ESRP) is based on the energy sensing strategy. Multiple strategy routing and substitute routing are both adopted in this paper. Referring to the level of the residual energy and the situation of energy consumption, different routes are chosen for packets transmission. The local maintenance is adopted, which can reduce packets retransmission effectively when the link breaks. We focus on the network lifetime most in all performances. The evaluation is done in comparison with other routing protocols on NS2 platform, and the simulation results show that this routing protocol can prolong the network lifetime and balance energy consumption effectively.

There are a great amount of various resources described in many different ways for service oriented grid environment, while traditional grid resource discovery methods could not fit more complex future grid system. Therefore, this paper proposes a novel grid resource discovery method based on association rule hypergraph partitioning algorithm which analyzes user behavior in history transaction records to provide personality service for user. And this resource discovery method gives a new way to improve resource retrieval and management in grid research.

With the aim to improve the effectiveness of SAWSDL service discovery, this paper proposes a novel discovery method for SAWSDL services, which is based on the matchmaking of so-called fine-grained data semantics that is defined via sets of atomic elements with built-in data types. The fine-grained data semantics can be obtained by a transformation algorithm that decomposes parameters at message level into a set of atomic elements, considering the characteristics of SAWSDL service structure and semantic annotations. Then, a matchmaking algorithm is proposed for the matching of fine-grained data semantics, which avoids the complex and expensive structural matching at the message level. The fine-grained data semantics is transparent to the specific data structure of message-level parameters, therefore, it can help to match successfully similar Web services with different data structures of parameters. Moreover, a comprehensive measure is proposed by considering together several important components of SAWSDL service descriptions at the same time. Finally, this method is evaluated on SAWSDL service discovery test collection SAWSDL-TC2 and compared with other SAWSDL matchmakers. The experimental results show that our method can improve the effectiveness of SAWSDL service discovery with low average query response time. The results imply that fine-grained parameters fit to represent the data semantics of SAWSDL services, especially when data structures of parameters are not important for semantics.

Recently, to track and relate news documents from several sources, association rule mining has been applied due to its performance and scalability. This paper presents an empirical investigation on how term representation basis, term weighting, and association measure affects the quality of relations discovered among news documents. Twenty four combinations initiated by two term representation bases, four term weightings, and three association measures are explored with their results compared to human judgment of three-level relations: completely related, somehow related, and unrelated relations. The performance evaluation is conducted by comparing the top-k results of each combination to those of the others using so-called rank-order mismatch (ROM). The experimental results indicate that a combination of bigram (BG), term frequency with inverse document frequency (TFIDF) and confidence (CONF), as well as a combination of BG, TFIDF and conviction (CONV), achieves the best performance to find the related documents by placing them in upper ranks with 0.41% ROM on top-50 mined relations. However, a combination of unigram (UG), TFIDF and lift (LIFT) performs the best by locating irrelevant relations in lower ranks (top-1100) with 9.63% ROM. A detailed analysis on the number of the three-level relations with regard to their rankings is also performed in order to examine the characteristic of the resultant relations. Finally, a discussion and an error analysis are given.

Multi-hop Wireless LAN-based mesh network (WMN) provides high capacity and self-configuring capabilities. Due to data forwarding and path selection based on MAC address, WMN requires additional operations to achieve global connectivity using IPv6 address. The neighbor discovery operation over WLAN mesh networks requires repeated all-node broadcasting and this gives rise to a big burden in the entire mesh networks. In this letter, we propose the proxy neighbor discovery scheme for optimized IPv6 communication over WMN to reduce network overhead and communication latency. Using simulation experiments, we show that the control overhead and communication setup latency can be significantly reduced using the proxy-based neighbor discovery mechanism.

In this letter, we present a route discovery protocol for ad hoc multi-hop cellular networks which uses directional information towards the base station. The proposed protocol, based on the reactive approach, reduces flooding as much as possible. To quantify this, we analyze its performance in terms of how much progress it makes per hop and how much reduction in routing packet number it achieves per route discovery. The analytical, as well as simulation, results demonstrate that the proposed protocol significantly reduces flooding overheads and finds a route to the base station in a robust manner.

An Optical Line Terminal (OLT) needs to find and register newly connected Optical Network Units (ONUs) in the proposed Ethernet Optical Switched Access Network (E-OSAN) as well as the Ethernet Passive Optical Network (E-PON). In this discovery process, OLT measures round trip time (RTT) between OLT and each ONU and then assigns a Logical Link Identification (LLID) to each ONU. For E-OSAN, the conventional discovery method takes up to N discovery periods for OLT to register all ONUs, where N denotes the number of switch ports of the Optical Switching Module (OSM). This paper proposes an efficient method that completes discovery in just one period. This paper also evaluates the maximum ranging completion time of the proposed discovery method in a comparison with E-PON.

Location Based Services (LBS) are expected to become one of the major drivers of ubiquitous services due to recent inception of GPS-enabled mobile devices, the development of Web2.0 paradigm, and emergence of 3G broadband networks. Having this vision in mind, Community Context-attribute-oriented Collaborative Information Environment (CCCIE) based Autonomous Decentralized Community System (ADCS) is proposed to enable provision of services to specific users in specific place at specific time considering various context-attributes. This paper presents autonomous community construction technology that share service discovered by one member among others in flexible way to improve timeliness and reduce network cost. In order to meet crucial goal of real-time and context-aware community construction (provision of service/ service information to users with common interests), and defining flexible service area in highly dynamic operating environment of ADCS, proposed progressive ripple based service discovery technique introduces novel idea of snail's pace and steady advancing search followed by swift boundary confining mechanism; while service area construction shares the discovered service among members in defined area to further improve timeliness and reduce network cost. Analysis and empirical results verify the effectiveness of the proposed technique.

Recently, Kempf and Koodli have proposed a security protocol for Fast Mobile IPv6 (FMIPv6). Through the SEcure Neighbor Discovery (SEND) protocol, it achieves secure distribution of a handover key, and consequently becomes a security standard for FMIPv6. However, it is still vulnerable to redirection attacks. In addition, due to the SEND protocol, it suffers from denial of service attacks and expensive computational cost. In this paper, we present a security protocol, which enhances Kempf-Koodli's one with the help of the AAA infrastructure.

A Policy-based Network Management (PBNM) in Mobile Ad-hoc Networks (MANETs) should be efficient and reliable. In this letter, we propose a mechanism for the policy-based management in ad hoc networks and we discuss methods to discover the Policy Decision Point (PDP), set the management area, and manage the movements of nodes in the PBNM system. Finally, we assess the results through simulations.

This paper proposes a MAC protocol for presence information discovery in ubiquitous networks. The proposed protocol is designed for proactive discovery in which wireless devices periodically broadcast packets containing presence information. The protocol is based on Framed Aloha. The objective of the protocol is to assure the discovery time of single-hop neighbors considering wireless collisions and also power consumption. In this paper, we show that the proposed protocol is able to assure specified discovery time in distributed networks with random topology.