An image processing engine is an important component in generating high quality images in video systems. Processing during capture and display are non-standard and vary from case by case, hence, the flexibility of image processing engines has turned out to be an important issue. The conventional hardware type of image processing engine such as an Application Specific Integrated Circuit (ASIC) is not applicable for this case. In order to increase design reusability and ease time-to-market pressures, Application Specific Instruction-set Processors (ASIP) which provide high flexibility and high computational efficiency have emerged as a promising solution. In this paper, we present two ASIPs. PXL ASIP, which has a reconfigurable multi bank memory module and an SIMD type computation pipeline, is designed for pixel level image processing, while 2D ASIP, which has slide register module and reconfigurable ALU modules, is designed for 2D image processing. PXL ASIP can perform 4 to 10 times faster compared to its base processor, and 2D ASIP can perform 5 to 43 times faster compared to its base processor.
Industrial applications such as automotive ones require a cheap communication mechanism to send out communication messages from node to node by their deadline time. This paper presents a design paradigm in which we optimize slot multiplexing of a FlexRay bus under hard real-time constraints so that we can minimize the operating frequency of the FlexRay bus. The reduction of the operating frequency of a FlexRay bus helps one to choose a slower and cheaper wire harness for building a distributed system. We formulate a slot multiplexing optimization problem under hard real-time constraints. We build an integer linear programming (ILP) model as a means for solving the slot multiplexing optimization problem. Our experimental results show that our design paradigm achieved a 72.7% smaller operating frequency at its best than the naive one.
With the recent rapid growth of social image hosting websites, such as Flickr, it is easier to construct a large database with social tagged images. We propose an unsupervised approach for automatic ranking social images to improve content-based social image retrieval. We construct an image-tag relationship graph model with both social images and tags. The approach extracts visual and textual information and combines them for ranking by propagating them through the graph links with an optimized mutual reinforcement process. We conduct experiments showing that our approach can successfully use social tags for ranking and improving content-based social image search results, and performs better than other approaches.
Operating systems (OSes) are crucial for achieving high availability of computer systems. Even if applications running on an operating system are highly available, a bug inside the kernel may result in a failure of the entire software stack. The objective of this study is to gain some insight into the development of the Linux kernel that is more resilient against software faults. In particular, this paper investigates the scope of error propagation. The propagation scope is process-local if the erroneous value is not propagated outside the process context that activated it. The scope is kernel-global if the erroneous value is propagated outside the process context that activated it. The investigation of the scope of error propagation gives us some insight into 1) defensive coding style, 2) reboot-less rejuvenation, and 3) general recovery mechanisms of the Linux kernel. For example, if most errors are process-local, we can rejuvenate the kernel without reboots because the kernel can be recovered simply by killing faulty processes. To investigate the scope of error propagation, we conduct an experimental campaign of fault injection on Linux 2.6.18, using a kernel-level fault injector widely used in the OS community. Our findings are (1) our target kernel (Linux 2.6.18) is coded defensively. This defensive coding style contributes to lower rates of error manifestation and kernel-global errors, (2) the scope of error propagation is mostly process-local in Linux, and (3) global propagation occurs with low probability. Even if an error corrupts a global data structure, other processes merely access to them.
A novel simplification method for GPS trajectory is presented in this paper. Trajectory simplification can greatly improve the efficiency of data analysis (e.g., querying, clustering). Based on the observation of information content contained by sampling data, we assume that (1) the sampling points on the boundary of MBR (Minimum Bounding Rectangle) contain more information content, (2) the bigger the area of MBR is, the more the points should be stored. We applied these two assumptions in our method to simplify trajectory online. Two main components of this method (i.e., divide/merge principle and selection strategy), are elaborated in the paper. Moreover, we define a new error metric — enclosed area metric — to evaluate the accuracy of simplified trajectories, which is proven more robust against the uncertainty of GPS. To implement this measure, we devise a practical algorithm of area calculation for self-intersecting polygons. Through comparing with other methods in a series of experiments over huge dataset, our method is proven effective and efficient.
Social image hosting websites such as Flickr provide services to users for sharing their images. Users can upload and tag their images or search for images by using keywords which describe image semantics. However various low quality tags in the user generated folksonomy tags have negative influences on image search results and user experience. To improve tag quality, we propose four approaches with one framework to automatically generate new tags, and rank the new tags as well as the existing raw tags, for both untagged and tagged images. The approaches utilize and integrate both textual and visual information, and analyze intra- and inter- probabilistic relationships among images and tags based on a graph model. The experiments based on the dataset constructed from Flickr illustrate the effectiveness and efficiency of our approaches.
We prove the NP-completeness of finding a Hamiltonian path in an N × N × N cube graph with turns exactly at specified lengths along the path. This result establishes NP-completeness of Snake Cube puzzles: folding a chain of N3 unit cubes, joined at face centers (usually by a cord passing through all the cubes), into an N × N × N cube. Along the way, we prove a universality result that zig-zag chains (which must turn every unit) can fold into any polycube after 4 × 4 × 4 refinement, or into any Hamiltonian polycube after 2 × 2 × 2 refinement.
Once upon a time, there were two puzzles. One was the Towers of Hanoi invented or introduced by Eduardo Lucas in 1883. The other was Spin-Out patented by William Keister in 1972. There are many stories about these puzzles. Some of these stories hint or claim that these puzzles have an intimate relationship with the Gray codes invented by Frank Gray in 1947. Here, we wish to show how these puzzles can be generalized and crossed to give puzzles for every base and for every number of pieces. The Gray relationship will become clearer when we describe the graphs associated with the puzzles and the graph labelings induced by the puzzles. These labelings will have the Gray property in the appropriate base. Counter to claims that Gray counting is needed to solve these puzzles, we describe counting algorithms which solve these puzzles using a standard binary counter. We also give recursive and iterative algorithms for these puzzles.
A picturesque maze is a kind of maze in which the solution path reveals a hidden black-and-white raster image. We propose here an algorithm to generate a picturesque maze of a given black-and-white raster image. Okamoto and Uehara proposed an algorithm to generate a picturesque maze by turning each original pixel into a 2-by-2 set of pixels. One drawback of the method is that the entrance and the exit are always adjacent. We propose a simple algorithm to generate a picturesque maze with any given endpoints for a 2-edge-connected input image.
This paper deals with a variation of crypt-arithmetics, called “arithmetical restorations.” Arithmetical restorations are problems dealing with the reconstruction of arithmetical sums from which various digits have been erased. We show the NP-completeness of a problem deciding whether a given instance of arithmetical restorations of multiplication sums has a solution or not.
Tantrix Match is a puzzle in which hexagonal tiles are arranged within a hexagonal lattice board in which there are some fixed tiles. Each tile has painted lines in three of four possible colors, and it is required that all lines that touch on adjacent tiles must match in color. The aim of this research is to determine the computational complexity of this puzzle, and we prove that the generalized Tantrix Match is NP-complete by reduction from the circuit-satisfiability problem (Circuit-SAT).
In social networks, nodes usually represent people and edges represent the relationship and connections between people. Ranking how important the nodes are with respect to some query nodes has a lot of applications in social networks. More often, people are interested in finding the Top-k most “relatively important” nodes with respect to some query nodes. A major challenge in this area of research is to define a function for measuring the “relative importance” between two nodes. In this paper, we present a measure called path probability to represent the connection strength of a between the ending node and the starting node. We proposed a measure of relative importance by using the sum of the path probabilities of all the “important” paths between a node with respect to a query node. Another challenge of computing the relative importance is the scalability issue. Most popular solutions are random walk based algorithms which involve matrix multiplication, and therefore are computationally too expensive for large graphs with millions of nodes. In this paper, by defining the path probability and introducing a small threshold value to determine whether a path is important or significant, we are able to ignore a lot of unimportant nodes so as to be able to efficiently identify the Top-k most relatively important nodes to the query nodes. Experiments are conducted over several synthetic and real graphs. The results are encouraging, and show a strong correlation between our approach and the well known random walk with restart algorithm.
In this paper we propose Block Device Layer with Automatic Parallelism Tuning (BDL-APT), a mechanism that maximizes the goodput of heterogeneous IP-based Storage Area Network (IP-SAN) protocols in long-fat networks. BDL-APT parallelizes data transfer using multiple IP-SAN sessions at a block device layer on an IP-SAN client, automatically optimizing the number of active IP-SAN sessions according to network status. A block device layer is a layer that receives read/write requests from an application or a file system, and relays those requests to a storage device. BDL-APT parallelizes data transfer by dividing aggregated read/write requests into multiple chunks, then transferring a chunk of requests on every IP-SAN session in parallel. BDL-APT automatically optimizes the number of active IP-SAN sessions based on the monitored network status using our parallelism tuning mechanism. We evaluate the performance of BDL-APT with heterogeneous IP-SAN protocols (NBD, GNBD and iSCSI) in a long-fat network. We implement BDL-APT as a layer of the Multiple Device driver, one of major software RAID implementations included in the Linux kernel. Through experiments, we demonstrate the effectiveness of BDL-APT with heterogeneous IP-SAN protocols in long-fat networks regardless of protocol specifics.
By using a dynamic VLAN feature of recent network equipment, we can configure a location-free network environment which can authenticate a user of a terminal and assign a VLAN for his/her terminal dynamically so that the user can connect his/her terminal to the same VLAN anywhere in the organization. However, on such a location-free network environment, it is difficult to use some location dependent services. One typical location dependent service is site license of an electronic journal (e-journal) that users can access the contents only if they are in specific locations. In this paper, we propose configuration of a location free network which can adapt location dependent services by devising the allocation of the VLAN-IDs and the subnet IP addresses. By this method, since no special equipment is required, it is possible to build a network system without extra cost. We configured the network system based on the proposed method on the campus network of Okayama University and confirmed the effectiveness and the practicability on accessing some site-licensed e-journals.
With proliferation of the Internet and its services, how to provide stable and efficient Internet services via reliable high-speed network has become an important issue. Multihomed network is attracted much attention to provide stable and efficient Internet services. In this paper, we focus on the multihoming method in the IPv6 environment. In the IPv6 environment, each host can be assigned multiple IP addresses from different ISPs on one network interface, thus the multihoming is relatively easier than that in the IPv4 environment. However, since many ISPs adopt ingress filtering for security concerns, a multihomed site should select a proper site-exit router according to the source IP address of the packet to communicate with the outside the site successfully. In most site-exit router selection methods, a kind of source IP address dependent routing method is introduced which has some problems in terms of high deployment cost and lack of fault-tolerance and so on.In this paper, we propose a new site-exit router selection method using the routing header which can indicate the router to pass through in the IPv6 environment. This method introduces two middlewares, one into the inside server and the other into the site-exit router. The one in the inside server attaches a routing header which indicates a specific site-exit router to pass through according to the source IP address of the packet, and the other in the site-exit router removes the attached routing header from the packet, thus the inside server can communicate with the outside the site successfully as usual. We also implemented a prototype system including the proposed inside server and the site-exit router and performed feature evaluation as well as performance evaluation. From the evaluation results, we confirmed the proposed method worked well and the overhead of the middlewares are acceptable for practical use in the real network environments.
In this paper, we propose a new architecture for parallel and distributed processing framework, “Jobcast, ” which enables data processing on a cloud style KVS database. Nowadays, many KVS (as known as Key Value Store) systems exist which achieve high scalability for data spaces among a huge number of computers. The Jobcast architecture is an extension which has the capability to execute “job” on KVS data nodes so that it can also achieve scalability of processing space. In this paper, we introduce the Jobcast architecture and describe how Jobcast improves performance of some KVS applications especially by reducing data transmission cost. We evaluate and discuss performance improvement for some example applications as well.
In this paper, we propose an account provision and management (APAM) architecture for messaging services such as web mail in an emergency such as a massive earthquake. The APAM architecture stably and continually provides people (users) who hope to confirm each other's safety in a stricken area with message services, even if mobile phone lines and fixed lines are unavailable. This is realized by automatically establishing an emergent line such as a satellite line and stably providing the services from a server (emergent server) in the evacuation area. The emergent server provides all users with an emergent account and authenticates the account in the evacuation area so as to avoid traffic congestion in the emergent line (low-bandwidth line). If some users already have their own account, the emergent server and the server on the Internet binds the emergent account with their account for receiving message data from their relatives as usual. Moreover, even if users move to other evacuation areas to seek their relatives, this APAM architecture allows users to continually use the services by updating the binding information of the account. We deployed a prototype system and conducted experiments to evaluate the APAM architecture. The experimental results show that the APAM architecture can stably and continually provide 1,000 users (typical capacity of the area) with an emergent account and messaging services simultaneously.
Energy conservation is an important global issue. The home is the third largest energy consumer, and 10% of the home energy use is standby power of home appliances. The proliferation of home networks increases the standby power. The conventional technologies for low networked standby power such as WoL require continuous AC power, as much as 0.5watts, to monitor wake-up signals. A large portion of the consumed power is due to the power loss in the AC-DC converter. Moreover, the technologies are applicable only to the specific network types such as Ethernet and IEEE802.11. We propose a solution to reduce the networked standby power down to zero virtually, regardless of the network type. For monitoring wake-up signals, the solution utilizes the pre-charged power in an ultra capacitor without using the AC power supply for almost all the time. In order to realize this idea, the solution also utilizes a unique and simple protocol dedicated only to the networked standby/wake-up functionality. This protocol enables the monitoring circuit to consume a very small amount of power, small enough for the capacitor to supply. The networked standby/wake-up functionality is easily combined with any conventional network application protocol by protocol address mapping. As one realization example of our solution, we implemented an experimental home A/V system which is integrated with an ultra low power wireless signal receiver and extended UPnP protocol. The system evaluation showed that our solution achieves the zero-watt networked standby while keeping network functionalities. Moreover, the analysis of the results based on a statistical survey shows that the practical networked standby power is 30mW when our solution is applied to a TV system, which corresponds to one seventeenth of a conventional technology, WoL. It means that our solution improves power consumption by 22% which corresponds to 1.11kg-CO2 emission reduction per year per product.
Conventional flow-level simulators use timescales around the round-trip time when numerically solving fluid-flow models for network simulations. In large-scale and high-speed network simulations, only understanding coarser behavior than that achieved with timescales around the round-trip time is sometimes sufficient for performance evaluation. In this paper, we propose a novel method for accelerating flow-level simulations; it omits timescale finer than that required by the performance evaluation. Through experiments, we investigate the effectiveness of the proposed method for accelerating flow-level simulations. Our findings show that the proposed method offers 60 times faster than the conventional flow-level simulator.
The Wideband InterNetworking engineering test and Demonstration Satellite (WINDS) has an ultra-high speed international Internet-based communication system. However, the characteristics (for example, transmission bit errors, large propagation delay) of its satellite communication markedly degrade the throughput of conventional TCP (TCP Reno). Therefore, the satellite communications should adopt an enhanced TCP which has been proposed for high-bandwidth and long-delay networks, and can utilize the resource of the satellite network at a maximum level. In this study, we have compared the performance of ten TCPs (TCP Reno and nine enhanced TCPs) by building an experimental environment of the satellite communication over WINDS. The measurement results have shown that TCP Hybla achieves the best performance among all TCPs in terms of the throughput of communication over WINDS. Therefore, TCP Hybla could be the best solution to communications established on WIND's satellite network. However, the congestion control of one TCP Hybla flow has not only suppressed the transmission speed of other flows of TCP Reno, but also prevented the windows size of other TCP Hybla flows from reaching the stable state when multiple TCP flows coexist on the same satellite link. This should be taken into account when using TCP Hybla.
Collaborative Decision Making (CDM) is a process of reaching consensus on a potential solution of an issue through the evaluation of the different possible alternatives. The web-based intelligent computational argumentation system allows concerned decision making agents to post their arguments on different alternatives, assign degree of strengths to their arguments and identify the most favorable alternative using our system over the internet. Agents are a group of people who participate in the argumentation process for the collaborative decision making process. Our system resolves the conflicts through intelligent argumentation and captures the rationale of the agents from their arguments. The exchange of information among the agents in the form of arguments helps them present their views and opinions and drives the group towards collective intelligence. In this article, we present an approach on how the intelligent argumentation based collaborative decision support system can facilitate the resolution of conflicts in air traffic management. It could enhance the Ground Delay Program (GDP) and help the Air Traffic Control System Command Center (ATCSCC) to take a better decision depending on the argumentation of Air Route Traffic Control Centers (ARTCC) and agents from different airlines.
In this paper we have presented a classification framework for classifying tweets relevant to some specific target sectors. Due to the imposed length restriction on an individual tweet, tweet classification faces some additional challenges which are not present in most other short text classification problems, needless to say in classification of standard written text. Hence, bag-of-word classifiers, which have been successfully leveraged for text classification in other domains, fail to achieve a similar level of accuracy in classifying tweets. In this paper, we have proposed a collocation feature selection algorithm for tweet classification. Moreover, we have proposed a strategy, built on our selected collocation features, for identifying and removing confounding outliers from a training set. An Evaluation on two real world datasets shows that the proposed model yields a better accuracy than the unigram model, uni-bigram model and also a partially supervised topic model on two different classification tasks.
The Domain Name System (DNS) is a key naming system used in the Internet. Recently, the deployment of IPv6 (especially after the World IPv6 Launch) and DNS prefetching in web browsers has significantly changed DNS usage. Furthermore, content delivery networks (CDNs) use complicated DNS configurations together with small TTL values to control their traffic. These three factors significantly increase DNS traffic. Thus, the importance of DNS traffic analysis has been increasing to properly maintain DNS operations. This paper presents an analysis of DNS full resolver traffic at the University of Tsukuba in Japan. What we found are 1) The deployment of IPv6 has increased queries from clients as much as 41%, 2) The deployment of CDNs increases the use of small TTL values, the use of CNAME resource records and the use of out-of-bailiwick DNS server names. Since these increases are making the DNS cache hit rate low and the DNS response slow without recognition by Internet users, this paper seeks to warn application designers of potential system design risks in current Internet applications.
The technologies used by attackers in the Internet environment are becoming more and more sophisticated. Of the many kinds of attacks, distributed scan attacks have become one of the most serious problems. In this study, we propose a novel method based on normal behavior modes of traffic to detect distributed scan attacks in darknet environments. In our proposed method, all the possible destination TCP and UDP ports are monitored, and when a port is attacked by a distributed scan, an alert is given. Moreover, the alert can have several levels reflecting the relative scale of the attack. To accelerate learning and updating the normal behavior modes and to realize rapid detection, an index is introduced, which is proved to be very efficient. The efficiency of our proposal is verified using real darknet traffic data. Although our proposal focuses on darknets, the idea can also be applied to ordinary networks.
Web-based malware attacks have become one of the most serious threats that need to be addressed urgently. Several approaches that have attracted attention as promising ways of detecting such malware include employing one of several blacklists. However, these conventional approaches often fail to detect new attacks owing to the versatility of malicious websites. Thus, it is difficult to maintain up-to-date blacklists with information for new malicious websites. To tackle this problem, this paper proposes a new scheme for detecting malicious websites using the characteristics of IP addresses. Our approach leverages the empirical observation that IP addresses are more stable than other metrics such as URLs and DNS records. While the strings that form URLs or DNS records are highly variable, IP addresses are less variable, i.e., IPv4 address space is mapped onto 4-byte strings. In this paper, a lightweight and scalable detection scheme that is based on machine learning techniques is developed and evaluated. The aim of this study is not to provide a single solution that effectively detects web-based malware but to develop a technique that compensates the drawbacks of existing approaches. The effectiveness of our approach is validated by using real IP address data from existing blacklists and real traffic data on a campus network. The results demonstrate that our scheme can expand the coverage/accuracy of existing blacklists and also detect unknown malicious websites that are not covered by conventional approaches.
A scan-path test is one of the useful design-for-test techniques, in which testers can observe and control registers inside the target LSI chip directly. On the other hand, the risk of side-channel attacks against cryptographic LSIs and modules has been pointed out. In particular, scan-based attacks which retrieve secret keys by analyzing scan data obtained from scan chains have been attracting attention. In this paper, we propose two scan-based attack methods against DES and Triple DES using scan signatures. Our proposed methods are based on focusing on particular bit-column-data in a set of scan data and observing their changes when giving several plaintexts. Based on this property, we introduce the idea of a scan signature first and apply it to DES cryptosystems. In DES cryptosystems, we can retrieve secret keys by partitioning the S-BOX process into eight independent sub-processes and reducing the number of the round key candidates from 248 to 26 × 8 = 512. In Triple DES cryptosystems, three secret keys are used to encrypt plaintexts. Then we retrieve them one by one, using the similar technique as in DES cryptosystems. Although some problems occur when retrieving the second/third secret key, our proposed method effectively resolves them. Our proposed methods can retrieve secret keys even if a scan chain includes registers except a crypto module and attackers do not know when the encryption is really done in the crypto module. Experimental results demonstrate that we successfully retrieve the secret keys of a DES cryptosystem using at most 32 plaintexts and that of a Triple DES cryptosystem using at most 36 plaintexts.
We developed a new information management system, Protein Experimental Information Management System (PREIMS), which has the ontology-based functions for quality control, validation, scalability, and information sharing. Its contents are mainly experimental protocols for the analyses of protein structures and functions, and their results. They are stored separately in the PREIMS database (DB), as the ontology based protocol data and the result data. The synchrotron experimental information was stored as the latter result data in Extensible Markup Language (XML). Furthermore we converted those protocols in the format of Resource Description Framework (RDF) for integration with other biological information resources.
More and more biomedical documents are digitally written and stored. To make the most of the rich resources, it is crucial to precisely locate the information pertinent to user's interests. An obstacle in finding information in natural language text is negations, which deny or reverse the meaning of a sentence. This is especially problematic in the biomedical domain since scientific findings and clinical records often contain negated expressions to state negative effects or the absence of symptoms. This paper reports on our work on a hybrid approach to negation identification combining statistical and heuristic approaches and describes an implementation of the approach, named NegFinder, as a Web service.
In this paper, we propose a novel method, named SCPSSMpred (Smoothed and Condensed PSSM based prediction), which uses a simplified position-specific scoring matrix (PSSM) for predicting ligand-binding sites. Although the simplified PSSM has only ten dimensions, it combines abundant features, such as amino acid arrangement, information of neighboring residues, physicochemical properties, and evolutionary information. Our method employs no predicted results from other classifiers as input, i.e., all features used in this method are extracted from the sequences only. Three ligands (FAD, NAD and ATP) were used to verify the versatility of our method, and three alternative traditional methods were also analyzed for comparison. All the methods were tested at both the residue level and the protein sequence level. Experimental results showed that the SCPSSMpred method achieved the best performance besides reducing 50% of redundant features in PSSM. In addition, it showed a remarkable adaptability in dealing with unbalanced data compared to other methods when tested on the protein sequence level. This study not only demonstrates the importance of reducing redundant features in PSSM, but also identifies sequence-derived hallmarks of ligand-binding sites, such that both the arrangements and physicochemical properties of neighboring residues significantly impact ligand-binding behavior.
To investigate how the use of photographs affects creativity, we have developed a system called GUNGEN-PHOTO, in which photographs are used to support idea generation. It consists of a collaborative workspace and personal workspaces and includes two main functions: photograph expansion for effectively extracting ideas from photographs, and outside comment addition for adding comments from personal workspaces. These functions are expected to increase the number of ideas generated. We conducted experiments on idea generation under the themes of “improvement” and “discovery, ” and found that more ideas were generated when photographs were used than when only text was used. We also found there were no significant differences in the quality of generated group between them.