Due to the increase in the volume of data and intensified concurrent requests, distributed caching is commonly used to manage high-concurrency requests and alleviate pressure on databases. However, there is limited research on distributed record mapping caching, and traditional caching algorithms have suboptimal resolution performance for mapping records that typically follow a long-tail distribution. To address the aforementioned issue, in this paper, we propose a recommendation-based adaptive auxiliary caching method, AC-REC, which delivers the primary cache record along with a list of additional cache records. The method uses request correlations as a basis for recommendations, customizes the number of additional cache entries provided, and dynamically adjusts the time-to-live. We conducted evaluations to compare the performance of our method against various benchmark strategies. The results show that our proposed method, as compared to the conventional LCE method, increased the cache hit ratio by an average of 20%, Moreover, this improvement is achieved while effectively utilizing the cache space. We believe that our strategy will contribute an effective solution to the related studies in both traditional network architecture and caching in paradigms like ICN.

In spatially distributed systems such as smart buildings and intelligent transportation systems, control of spatio-temporal patterns is an important issue. In this paper, we consider a finite-horizon optimal spatio-temporal pattern control problem where the pattern is specified by a signal spatio-temporal logic formula over finite traces, which will be called an SSTLf formula. We give the syntax and Boolean semantics of SSTLf. Then, we show linear encodings of the temporal and spatial operators used in SSTLf and we convert the problem into a mixed integer programming problem. We illustrate the effectiveness of this proposed approach through an example of a heat system in a room.

The previous communication-induced checkpointing may considerably induce worthless forced checkpoints because each process receiving messages cannot obtain sufficient information related to non-causal Z-paths. This paper presents an enhanced sender-based message logging protocol applicable to any communication-induced checkpointing to lead to a high decrease of the forced checkpointing overhead of communication-induced checkpointing in an effective way while permitting no useless checkpoint. The protocol allows each process sending a message to know the exact timestamp of the receiver of the message in its logging procedures without any extra message. Simulation verifies their great efficiency of overhead alleviation regardless of communication patterns.

We propose a system time synchronization method between ARM-based embedded Linux systems. The master Linux with reference clock sends its own system time to the slave Linux via Transmission Control Protocol communication along with a general-purpose input/output (GPIO) signal, and then the slave Linux corrects its own system time by the difference between its own system time at receiving the GPIO signal and the received reference time. The synchronization performance is significantly improved by compensating for the GPIO signal detection latency and the system time acquisition and setting latencies in Linux. These latencies are precisely measured by exploiting the function of Cycle Counter register in ARM coprocessor. Extensive experiments are performed with two ARM-based embedded Linux systems, and the results demonstrate the validity and performance of the proposed synchronization method.

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.

This article presents a universal and versatile model of multiservice overflow systems based on Hayward's concept. The model can be used to analyze modern telecommunications and computer networks, mobile networks in particular. The advantage of the proposed approach lies in its ability to analyze overflow systems with elastic and adaptive traffic, systems with distributed resources and systems with non-full-availability in primary and secondary resources.

In this paper, we consider the partial gathering problem of mobile agents in arbitrary networks. The partial gathering problem is a generalization of the (well-investigated) total gathering problem, which requires that all the agents meet at the same node. The partial gathering problem requires, for a given positive integer g, that each agent should move to a node and terminate so that at least g agents should meet at each of the nodes they terminate at. The requirement for the partial gathering problem is no stronger than that for the total gathering problem, and thus, we clarify the difference on the move complexity between them. First, we show that agents require Ω(gn+m) total moves to solve the partial gathering problem, where n is the number of nodes and m is the number of communication links. Next, we propose a deterministic algorithm to solve the partial gathering problem in O(gn+m) total moves, which is asymptotically optimal in terms of total moves. Note that, it is known that agents require Ω(kn+m) total moves to solve the total gathering problem in arbitrary networks, where k is the number of agents. Thus, our result shows that the partial gathering problem is solvable with strictly fewer total moves compared to the total gathering problem in arbitrary networks.

In this paper, we present a hybrid message logging protocol consisting of three modules for two-level hierarchical and distributed architectures to address the drawbacks of sender-based message logging. The first module reduces the number of in-group control messages and, the rest, the number of inter-group control messages while localizing recovery. In addition, it can distribute the load of logging and keeping inter-group messages to group members as evenly as possible. The simulation results show the proposed protocol considerably outperforms the traditional protocol in terms of message logging overhead and scalability.

All the existing sender-based message logging (SBML) protocols share a well-known limitation that they cannot tolerate concurrent failures. In this paper, we analyze the cause for this limitation in a unicast network environment, and present an enhanced SBML protocol to overcome this shortcoming while preserving the strengths of SBML. When the processes on different nodes execute a distributed application together in a broadcast network, this new protocol replicates the log information of each message to volatile storages of other processes within the same broadcast network. It may reduce the communication overhead for the log replication by taking advantage of the broadcast nature of the network. Simulation results show our protocol performs better than the traditional one modified to tolerate concurrent failures in terms of failure-free execution time regardless of distributed application communication pattern.

In this paper, we propose a communication-efficient top-k continuous query processing method on distributed local nodes where data are horizontally partitioned. A designated coordinator server takes the role of issuing queries from users to local nodes and delivering the results to users. The final results are requested via a top-k subscription which lets local nodes know which data and updates need to be returned to users. Our proposed method makes use of the active previously posed queries to identify a small set of needed top-k subscriptions. In addition, with the pre-indexed nodes' skylines, the number of local nodes to be subscribed can be significantly reduced. As a result, only a small number of subscriptions are informed to a small number of local nodes resulting in lower communication overhead. Furthermore, according to dynamic data updates, we also propose a method that prevents nodes from reporting needless updates and also maintenance procedures to preserve the consistency. The results of experiments that measure the volume of transferred data show that our proposed method significantly outperforms the previously proposed methods.

The excessively high temperature in a chip may cause circuit malfunction and performance degradation, and thus should be avoided to improve system reliability. In this paper, a novel oscillation-based on-chip thermal sensing architecture for dynamically adjusting supply voltage and clock frequency in System-on-a-Chip (SoC) is proposed. It is shown that the oscillation frequency of a ring oscillator reduces linearly as the temperature rises, and thus provides a good on-chip temperature sensing mechanism. An efficient Dynamic Voltage-to-Frequency Scaling (DF2VS) algorithm is proposed to dynamically adjust supply voltage according to the oscillation frequencies of the ring oscillators distributed in SoC so that thermal sensing can be carried at all potential hot spots. An on-chip Dynamic Voltage Scaling or Dynamic Voltage and Frequency Scaling (DVS or DVFS) monitor selects the supply voltage level and clock frequency according to the outputs of all thermal sensors. Experimental results on SoC benchmark circuits show the effectiveness of the algorithm that a 10% reduction in supply voltage alone can achieve about 20% power reduction (DVS scheme), and nearly 50% reduction in power is achievable if the clock frequency is also scaled down (DVFS scheme). The chip temperature will be significant lower due to the reduced power consumption.

We propose a fast and resource-efficient agreement protocol on a request set, which is used to realize Byzantine fault tolerant server replication. Although most existing randomized protocols for Byzantine agreement exploit a modular approach, that is, a combination of agreement on a bit value and a reduction of request set values to the bit values, our protocol directly solves the multi-valued agreement problem for request sets. We introduce a novel coin tossing scheme to select a candidate of an agreed request set randomly. This coin toss allows our protocol to reduce resource consumption and to attain faster response time than the existing representative protocols.

We propose a new method that accelerates asynchronous Byzantine Fault Tolerant (BFT) protocols designed on the principle of state machine replication. State machine replication protocols ensure consistency among replicas by applying operations in the same order to all of them. A naive way to determine the application order of the operations is to repeatedly execute the BFT consensus to determine the next executed operation, but this may introduce inefficiency caused by waiting for the completion of the previous execution of the consensus protocol. To reduce this inefficiency, our method allows parallel execution of the consensuses while keeping consistency of the consensus results at the replicas. In this paper, we also prove the correctness of our method and experimentally compare it with the existing method in terms of latency and throughput. The evaluation results show that our method makes a BFT protocol three or four times faster than the existing one when some machines or message transmissions are delayed.

Checkpoint-rollback recovery, which is a universal method for restoring distributed systems after faults, requires a sophisticated snapshot algorithm especially if the systems are large-scale, since repeatedly taking global snapshots of the whole system requires unacceptable communication cost. As a sophisticated snapshot algorithm, a partial snapshot algorithm has been introduced that takes a snapshot of a subsystem consisting only of the nodes that are communication-related to the initiator instead of a global snapshot of the whole system. In this paper, we modify the previous partial snapshot algorithm to create a new one that can take a partial snapshot more efficiently, especially when multiple nodes concurrently initiate the algorithm. Experiments show that the proposed algorithm greatly reduces the amount of communication needed for taking partial snapshots.

The implementation and experimental evaluations of distributed zero-forcing beamforming (DZFBF) for downlink multi-user multiple-input multiple-output (DL MU-MIMO) systems are presented. In DZFBF, multiple access points (APs) transmit to own desired stations (STAs) at the same time and using the same frequency channel while mitigating inter-cell interference. To clarify the performance and feasibility of DZFBF, we develop a real-time transmission testbed that includes two APs and four STAs; all are implemented using field programmable gate array. For real-time transmission, we also implement a simple weight generation process based on ZF weight using channel state information which is fed back from STAs; it is an extension of the weight generation approach used in DL MU-MIMO systems. By using our testbed, we demonstrate the real-time transmission performance in actual indoor multi-cell environments. These results indicate that DL DZFBF is more effective than DL MU-MIMO with time division multiple access.

Communication-induced checkpointing (CIC) has two main advantages: first, it allows processes in a distributed computation to take asynchronous checkpoints, and secondly, it avoids the domino effect. To achieve these, CIC algorithms piggyback information on the application messages and take forced local checkpoints when they recognize potentially dangerous patterns. The main disadvantages of CIC algorithms are the amount of overhead per message and the induced storage overhead. In this paper we present a communication-induced checkpointing algorithm called Scalable Fully-Informed (S-FI) that attacks the problem of message overhead. For this, our algorithm modifies the Fully-Informed algorithm by integrating it with the immediate dependency principle. The S-FI algorithm was simulated and the result shows that the algorithm is scalable since the message overhead presents an under-linear growth as the number of processes and/or the message density increase.

We propose a flexible and scalable architecture for a network controller platform used for OpenFlow. The OpenFlow technology was proposed as a means for researchers, network service creators, and others to easily design, test, and virtually deploy their innovative ideas in a large network infrastructure, which will accelerate research activities on Future Internet architectures. The technology enables the independent evolution of the network control plane and the data plane. Rather than having programmability within each network node, the separated OpenFlow controller provides network control through pluggable software. Our proposed network controller architecture will enable researchers to use their own software to control their own virtual networks. Flexibility and scalability were achieved by designing the network controller as a modularized and distributed system on a cluster of servers. Testing showed that a group of servers can efficiently cooperate to serve as a scalable OpenFlow controller. Testing using the nationwide JGN2plus network demonstrated that high-definition video can be delivered through OpenFlow-based point-to-point and point-to-multipoint paths.

Sender-based message logging (SBML) with checkpointing has its well-known beneficial feature, lowering highly failure-free overhead of synchronous logging with volatile logging at sender's memory. This feature encourages it to be applied into many distributed systems as a low-cost transparent rollback recovery technique. However, the original SBML recovery algorithm may no longer be progressing in some transient communication error cases. This paper proposes a consistent recovery algorithm to solve this problem by piggybacking small log information for unstable messages received on each acknowledgement message for returning the receive sequence number assigned to a message by its receiver. Our algorithm also enables all messages scheduled to be sent, but delayed because of some preceding unstable messages to be actually transmitted out much earlier than the existing ones.

Multiple-input multiple-output (MIMO) repeater systems have been discussed in several published papers. When a repeater has only one antenna element, the propagation environment is called keyhole. In this kind of scenario the achievable channel capacity and link quality are decreased. Another limit is when the number of the antenna elements of a repeater is larger than that of a MIMO transceiver, the channel capacity cannot be increased. In this paper, in order to obtain an upper bound of the channel capacity, we express a propagation process of the distributed MIMO repeater system with amplify-and-forward method by the numerical formular, and optimize the position of each repeater.

In a WSAN (Wireless Sensor and Actuator Network), most resources, including sensors and actuators, are designed for certain applications in a dedicated environment. Many researchers have proposed to use of gateways to infer and annotate heterogeneous data; however, such centralized methods produce a bottlenecking network and computation overhead on the gateways that causes longer response time in activity processing, worsening performance. This work proposes two distribution inference mechanisms: regionalized and sequential inference mechanisms to reduce the response time in activity processing. Finally, experimental results for the proposed inference mechanisms are presented, and it shows that our mechanisms outperform the traditional centralized inference mechanism.