Satellite communications (SATCOM) systems play important roles in wireless communication systems. In the future, they will be required to accommodate rapidly increasing communication requests from various types of users. Therefore, we propose a framework for efficient resource management in large-scale SATCOM systems that integrate multiple satellites. Such systems contain hundreds of thousands of communication satellites, user terminals, and gateway stations; thus, our proposed framework enables simpler and more reliable communication between users and satellites. To manage and control this system efficiently, we formulate an optimization problem that designs the network structure and allocates communication resources for a large-scale SATCOM system. In this mixed integer programming problem, we allow the cost function to be a combination of various factors so that SATCOM operators can design the network according to their individual management strategies. These factors include the total allocated bandwidth to users, the number of satellites and gateway stations to be used, and the number of total satellite handovers. Our numerical simulations show that the proposed management strategy outperforms a conventional strategy in which a user can connect to only one specific satellite determined in advance. Furthermore, we determine the effect of the number of satellites in the system on overall system performance.

This paper proposes a visual analytics (VA) interface for time-series data so that it can solve the problems arising from the property of time-series data: a collision between interaction and animation on the temporal aspect, collision of interaction between the temporal and spatial aspects, and the trade-off of exploration accuracy, efficiency, and scalability between different visualization methods. To solve these problems, this paper proposes a VA interface that can handle temporal and spatial changes uniformly. Trajectories can show temporal changes spatially, of which direct manipulation enables to examine the relationship among objects either at a certain time point or throughout the entire time range. The usefulness of the proposed interface is demonstrated through experiments.

Information and communication technologies have improved the quality of intelligent transportation systems (ITS). By estimating from cellular floating vehicle data (CFVD) is more cost-effective, and easier to acquire than traditional ways. This study proposes a cell probe (CP)-based method to analyse the cellular network signals (e.g., call arrival, handoff, and location update), and regression models are trained for vehicle speed estimation. In experiments, this study compares the practical traffic information of vehicle detector (VD) with the estimated traffic information by the proposed methods. The experiment results show that the accuracy of vehicle speed estimation by CP-based method is 97.63%. Therefore, the CP-based method can be used to estimate vehicle speed from CFVD for ITS.

This paper presents decentralized multi-authority attribute-based encryption and signature (DMA-ABE and DMA-ABS) schemes, in which no central authority exists and no global coordination is required except for the setting of a parameter for a prime order bilinear group and a hash function, which can be available from public documents, e.g., ISO and FIPS official documents. In the proposed DMA-ABE and DMA-ABS schemes, every process can be executed in a fully decentralized manner; any party can become an authority and issue a piece for a secret key to a user without interacting with any other party, and each user obtains a piece of his/her secret key from the associated authority without interacting with any other party. While enjoying such fully decentralized processes, the proposed schemes are still secure against collusion attacks, i.e., multiple pieces issued to a user by different authorities can form a collusion resistant secret key, composed of these pieces, of the user. The proposed ABE scheme is the first DMA-ABE for non-monotone relations (and more general relations), which is adaptively secure under the decisional linear (DLIN) assumption in the random oracle model. This paper also proposes the first DMA-ABS scheme for non-monotone relations (and more general relations), which is fully secure, adaptive-predicate unforgeable and perfect private, under the DLIN assumption in the random oracle model. DMA-ABS is a generalized notion of ring signatures. The efficiency of the proposed DMA-ABE and DMA-ABS schemes is comparable to those of the existing practical ABE and ABS schemes with comparable relations and security.

We propose an image identification scheme for double-compressed encrypted JPEG images that aims to identify encrypted JPEG images that are generated from an original JPEG image. To store images without any visual sensitive information on photo sharing services, encrypted JPEG images are generated by using a block-scrambling-based encryption method that has been proposed for Encryption-then-Compression systems with JPEG compression. In addition, feature vectors robust against JPEG compression are extracted from encrypted JPEG images. The use of the image encryption and feature vectors allows us to identify encrypted images recompressed multiple times. Moreover, the proposed scheme is designed to identify images re-encrypted with different keys. The results of a simulation show that the identification performance of the scheme is high even when images are recompressed and re-encrypted.

In this article, we propose a data framework for edge computing that allows developers to easily attain efficient data transfer between mobile devices or users. We propose a distributed key-value storage platform for edge computing and its explicit data distribution management method that follows the publish/subscribe relationships specific to applications. In this platform, edge servers organize the distributed key-value storage in a uniform namespace. To enable fast data access to a record in edge computing, the allocation strategy of the record and its cache on the edge servers is important. Our platform offers distributed objects that can dynamically change their home server and allocate cache objects proactively following user-defined rules. A rule is defined in a declarative manner and specifies where to place cache objects depending on the status of the target record and its associated records. The system can reflect record modification to the cached records immediately. We also integrate a push notification system using WebSocket to notify events on a specified table. We introduce a messaging service application between mobile appliances and several other applications to show how cache rules apply to them. We evaluate the performance of our system using some sample applications.

Group signatures are signatures providing signer anonymity where signers can produce signatures on behalf of the group that they belong to. Although such anonymity is quite attractive considering privacy issues, it is not trivial to check whether a signer has been revoked or not. Thus, how to revoke the rights of signers is one of the major topics in the research on group signatures. In particular, scalability, where the signing and verification costs and the signature size are constant in terms of the number of signers N, and other costs regarding signers are at most logarithmic in N, is quite important. In this paper, we propose a revocable group signature scheme which is currently more efficient compared to previous all scalable schemes. Moreover, our revocable group signature scheme is secure under simple assumptions (in the random oracle model), whereas all scalable schemes are secure under q-type assumptions. We implemented our scheme by employing a Barreto-Lynn-Scott curve of embedding degree 12 over a 455-bit prime field (BLS-12-455), and a Barreto-Naehrig curve of embedding degree 12 over a 382-bit prime field (BN-12-382), respectively, by using the RELIC library. We showed that the online running times of our signing algorithm were approximately 14msec (BLS-12-455) and 11msec (BN-12-382), and those of our verification algorithm were approximately 20msec (BLS-12-455) and 16msec (BN-12-382), respectively. Finally, we showed that our scheme (with a slight extension) is applied to an identity management system proposed by Isshiki et al.

MQTT is one of the promising protocols for various data exchange in IoT environments. Typically, those environments have a characteristic called “edge-heavy”, which means that things at the network edge generate a massive volume of data with high locality. For handling such edge-heavy data, an architecture of placing multiple MQTT brokers at the network edges and making them cooperate with each other is quite effective. It can provide higher throughput and lower latency, as well as reducing consumption of cloud resources. However, under this kind of architecture, heterogeneity could be a vital issue. Namely, an appropriate product of MQTT broker could vary according to the different environment of each network edge, even though different products are hard to cooperate due to the MQTT specification providing no interoperability between brokers. In this paper, we propose Interworking Layer of Distributed MQTT brokers (ILDM), which enables arbitrary kinds of MQTT brokers to cooperate with each other. ILDM, designed as a generic mechanism independent of any specific cooperation algorithm, provides APIs to facilitate development of a variety of algorithms. By using the APIs, we also present two basic cooperation algorithms. To evaluate the usefulness of ILDM, we introduce a benchmark system which can be used for both a single broker and multiple brokers. Experimental results show that the throughput of five brokers running together by ILDM is improved 4.3 times at maximum than that of a single broker.

Particle swarm optimization (PSO) is a swarm intelligence algorithm and has good search performance and simplicity in implementation. Because of its properties, PSO has been applied to various optimization problems. However, the search performance of the classical PSO (CPSO) depends on reference frame of solution spaces for each objective function. CPSO is an invariant algorithm through translation and scale changes to reference frame of solution spaces but is a rotationally variant algorithm. As such, the search performance of CPSO is worse in solving rotated problems than in solving non-rotated problems. In the reference frame invariance, the search performance of an optimization algorithm is independent on rotation, translation, or scale changes to reference frame of solution spaces, which is a property of preferred optimization algorithms. In our previous study, piecewise-linear particle swarm optimizer (PPSO) has been proposed, which is effective in solving rotated problems. Because PPSO particles can move in solution spaces freely without depending on the coordinate systems, PPSO algorithm may have rotational invariance. However, theoretical analysis of reference frame invariance of PPSO has not been done. In addition, although behavior of each particle depends on PPSO parameters, good parameter conditions in solving various optimization problems have not been sufficiently clarified. In this paper, we analyze the reference frame invariance of PPSO theoretically, and investigated whether or not PPSO is invariant under reference frame alteration. We clarify that control parameters of PPSO which affect movement of each particle and performance of PPSO through numerical simulations.

Adaptive Volterra filters (AVFs) are usually used to identify nonlinear systems, such as loudspeaker systems, and ordinary adaptive algorithms can be used to update the filter coefficients of AVFs. However, AVFs require huge computational complexity even if the order of the AVF is constrained to the second order. Improving calculation efficiency is therefore an important issue for the real-time implementation of AVFs. In this paper, we propose a novel sub-band AVF with high calculation efficiency for second-order AVFs. The proposed sub-band AVF consists of four parts: input signal transformation for a single sub-band AVF, tap length determination to improve calculation efficiency, switching the number of sub-bands while maintaining the estimation accuracy, and an automatic search for an appropriate number of sub-bands. The proposed sub-band AVF can improve calculation efficiency for which the dominant nonlinear components are concentrated in any frequency band, such as loudspeakers. A simulation result demonstrates that the proposed sub-band AVF can realize higher estimation accuracy than conventional efficient AVFs.

This paper focuses on power-area trade-off axis to memory systems. Compared with the power-performance-area trade-off application on the traditional high performance cache, this paper focuses on the edge processing environment which is becoming more and more important in the Internet of Things (IoT) era. A new power-oriented trade-off is proposed for on-chip cache architecture. As a case study, this paper exploits a good energy efficiency of Standard-Cell Memory (SCM) operating in a near-threshold voltage region and a good area efficiency of Static Random Access Memory (SRAM). A hybrid 2-level on-chip cache structure is first introduced as a replacement of 6T-SRAM cache as L0 cache to save the energy consumption. This paper proposes a method for finding the best capacity combination for SCM and SRAM, which minimizes the energy consumption of the hybrid cache under a specific cache area constraint. The simulation result using a 65-nm process technology shows that up to 80% energy consumption is reduced without increasing the die area by replacing the conventional SRAM instruction cache with the hybrid 2-level cache. The result shows that energy consumption can be reduced if the area constraint for the proposed hybrid cache system is less than the area which is equivalent to a 8kB SRAM. If the target operating frequency is less than 100MHz, energy reduction can be achieved, which implies that the proposed cache system is suitable for low-power systems where a moderate processing speed is required.

This paper constructs packet-oriented erasure correcting codes and their systematic forms for the distributed storage systems. The proposed codes are encoded by exclusive OR and bit-level shift operation. By the shift operation, the encoded packets are slightly longer than the source packets. This paper evaluates the extra length of the encoded packets, called overhead, and shows that the proposed codes have smaller overheads than the zigzag decodable codes, which are existing codes using bit-level shift operation and exclusive OR.

Real-time 3D players tracking plays an important role in sports analysis, especially for the live services of sports broadcasting, which have a strict limitation on processing time. For these kinds of applications, 3D trajectories of players contribute to high-level game analysis such as tactic analysis and commercial applications such as TV contents. Thus real-time implementation for 3D players tracking is expected. In order to achieve real-time for 60fps videos with high accuracy, (that means the processing time should be less than 16.67ms per frame), the factors that limit the processing time of target algorithm include: 1) Large image area of each player. 2) Repeated processing of multiple players in multiple views. 3) Complex calculation of observation algorithm. To deal with the above challenges, this paper proposes a representative spatial selection and temporal combination based real-time implementation for multi-view volleyball players tracking on the GPU device. First, the representative spatial pixel selection, which detects the pixels that mostly represent one image region to scale down the image spatially, reduces the number of processing pixels. Second, the representative temporal likelihood combination shares observation calculation by using the temporal correlation between images so that the times of complex calculation is reduced. The experiments are based on videos of the Final and Semi-Final Game of 2014 Japan Inter High School Games of Men's Volleyball in Tokyo Metropolitan Gymnasium. On the GPU device GeForce GTX 1080Ti, the tracking system achieves real-time on 60fps videos and keeps the tracking accuracy higher than 97%.

File systems based on persistent memory deploy Copy-on-Write (COW) or logging to guarantee data consistency. However, COW has a write amplification problem and logging has a double write problem. Both COW and logging increase write traffic on persistent memory. In this work, we present adaptive differential logging and zero-copy logging for persistent memory. Adaptive differential logging applies COW or logging selectively to each block. If the updated size of a block is smaller than or equal to half of the block size, we apply logging to the block. If the updated size of a block is larger than half of the block size, we apply COW to the block. Zero-copy logging treats an user buffer on persistent memory as a redo log. Zero-copy logging does not incur any additional data copy. We implement adaptive differential logging and zero-copy logging on both NOVA and PMFS file systems. Our measurement on real workloads shows that adaptive differential logging and zero-copy logging get 150.6% and 149.2% performance improvement over COW, respectively.

The latency and the energy consumption of DRAM are serious concerns because (1) the latency has not improved much for decades and (2) recent machines have huge capacity of main memory. Device-level studies reduce them by shortening the wait time of DRAM internal operations so that they finish fast and consume less energy. Applying these techniques aggressively to achieve approximate memory is a promising direction to further reduce the overhead, given that many data-center applications today are to some extent robust to bit-flips. To advance research on approximate memory, it is required to evaluate its effect to applications so that both researchers and potential users of approximate memory can investigate how it affects realistic applications. However, hardware simulators are too slow to run workloads repeatedly with different parameters. To this end, we propose a lightweight method to evaluate effect of approximate memory. The idea is to count the number of DRAM internal operations that occur to approximate data of applications and calculate the probability of bit-flips based on it, instead of using heavy-weight simulators. The evaluation shows that our system is 3 orders of magnitude faster than cycle accurate simulators, and we also give case studies of evaluating effect of approximate memory to some realistic applications.

Personalized trip planning is a challenging problem given that places of interest should be selected according to user preferences and sequentially arranged while satisfying various constraints. In this study, we aimed to model various uncertain aspects that should be considered during trip planning and efficiently generate personalized plans that maximize user satisfaction based on preferences and constraints. Specifically, we propose a probabilistic itinerary evaluation model based on a hybrid temporal Bayesian network that determines suitable itineraries considering preferences, constraints, and uncertain environmental variables. The model retrieves the sum of time-weighted user satisfaction, and ant colony optimization generates the trip plan that maximizes the objective function. First, the optimization algorithm generates candidate itineraries and evaluates them using the proposed model. Then, we improve candidate itineraries based on the evaluation results of previous itineraries. To validate the proposed trip planning approach, we conducted an extensive user study by asking participants to choose their preferred trip plans from options created by a human planner and our approach. The results show that our approach provides human-like trip plans, as participants selected our generated plans in 57% of the pairs. We also evaluated the efficiency of the employed ant colony optimization algorithm for trip planning by performance comparisons with other optimization methods.

We propose a method to realize a subjective super-resolution on a high-speed LED display, which dynamically shows a set of four neighboring pixels on every LED pixel. We have experimentally confirmed the subjective super-resolution effect. This paper proposes a subjective super-resolution hypothesis in human visual system and reports simulation results with pseudo fixation eye movements.

The least mean squares (LMS) algorithm has been widely used for adaptive filtering because of easily implementing at a computational complexity of O(2N) where N is the number of taps. The drawback of the LMS algorithm is that its performance is sensitive to the scaling of the input. The normalized LMS (NLMS) algorithm solves this problem on the LMS algorithm by normalizing with the sliding-window power of the input; however, this normalization increases the computational cost to O(3N) per iteration. In this work, we derive a new formula to strictly perform the NLMS algorithm at a computational complexity of O(2N), that is referred to as the C-NLMS algorithm. The derivation of the C-NLMS algorithm uses the H∞ framework presented previously by one of the authors for creating a unified view of adaptive filtering algorithms. The validity of the C-NLMS algorithm is verified using simulations.

Many kinds of questionnaires, testing, and voting are performed in some completely electronic ways to do questions and answers on the Internet as Web applications, i.e. e-questionnaire systems, e-testing systems, and e-voting systems. Because there is no unified communication tool among the stakeholders of e-questionnaire, e-testing, and e-voting systems, until now, all the e-questionnaire, e-testing, and e-voting systems are designed, developed, used, and maintained in various ad hoc ways. As a result, the stakeholders are difficult to communicate to implement the systems, because there is neither an exhaustive requirement list to have a grasp of the overall e-questionnaire, e-testing, and e-voting systems nor a standardized terminology for these systems to avoid ambiguity. A general-purpose specification language to provide a unified description way for specifying various e-questionnaire, e-testing, and e-voting systems can solve the problems such that the stakeholders can refer to and use the complete requirements and standardized terminology for better communications, and can easily and unambiguously specify all the requirements of systems and services of e-questionnaire, e-testing, and e-voting, even can implement the systems. In this paper, we propose the first specification language, named “QSL,” with a standardized, consistent, and exhaustive list of requirements for specifying various e-questionnaire, e-testing, and e-voting systems such that the specifications can be used as the precondition of automatically generating e-questionnaire, e-testing, and e-voting systems. The paper presents our design addressing that QSL can specify all the requirements of various e-questionnaire, e-testing, and e-voting systems in a structured way, evaluates its effectiveness, performs real applications using QSL in case of e-questionnaire, e-testing, and e-voting systems, and shows various QSL applications for providing convenient QSL services to stakeholders.

As a generalization of perfect nonlinear (PN) functions, zero-difference balanced (ZDB) functions play an important role in coding theory, cryptography and communications engineering. Inspired by a foregoing work of Liu et al. [1], we present a class of ZDB functions with new parameters based on the cyclotomy in finite fields. Employing these ZDB functions, we obtain simultaneously optimal constant composition codes and perfect difference systems of sets.