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Adaptive streaming allows for dynamic adaptation of the bitrate to varying network conditions, to guarantee the best user experience. Adaptive bitrate algorithms face a significant challenge in correctly estimating the throughput, as the throughput varies widely over time. The current throughput estimation methods cannot distinguish between throughput fluctuations of different amplitude and frequency. In this paper, we propose a throughput estimation method that accurately estimates the throughput based on previous throughput samples. It is robust to short term and small fluctuations, and sensitive to large fluctuations in throughput. Furthermore, we propose a rate adaptive algorithm for video on demand (VoD) services that selects the quality of the video based on the estimated throughput and playback buffer occupancy. The objective of the rate adaptive algorithms is to guarantee high video quality to improve user experience. The proposed algorithm dynamically adjusts the quality level of the video stream. The proposed method selects high quality video segments, while minimizing the risk of playback interruption. Furthermore, the proposed method minimizes the frequency of video rate changes. We show that the algorithm smoothly switches the video rate to improve user experience. Furthermore, we determine that it efficiently utilizes network resources to achieve a high video rate; competing HTTP clients achieve equitable video rates. We also confirm that variations in the playback buffer size and segment duration do not affect the performance of the proposed algorithm. [ABSTRACT FROM AUTHOR]

A method for evaluation of the performance of the disk subsystem of a data buffering and transmission system and results of experimental studies of the performance of the disk subsystem according to the developed method are presented. A conclusion is drawn on the reasonability of the use of hard-disk drives that provide the required read/write rates with a sufficiently high level of reliability in prospective development of the modern high-capacity NearLine SAS (NL-SAS). [ABSTRACT FROM AUTHOR]

The buffer allocation problem concerning the size and location of storage between the stages of a flow line is a critical research area in the design of production lines. In this study, a production system consisting of two unreliable stages and a buffer between them is considered; the first stage incorporates two identical machines in parallel and the second stage consists of a single machine. A simulation model is designed and used to evaluate the effect of the buffer capacity and the repair rates of machines on production line efficiency. The results revealed the capacity of buffer that yields the maximum production line efficiency with various repair rate values. [ABSTRACT FROM AUTHOR]

Current high-level synthesis (HLS) tools for the automatic design of computing hardware perform excellently for the synthesis of computation kernels, but they often do not optimize memory bandwidth. As accessing memory is a bottleneck in many algorithms, the performance of the generated circuit could benefit substantially from memory access optimization. In this paper, we present a method and a tool to automate the optimization of memory accesses to array data in HLS by introducing local memory tailored perfectly to store only the data that are used repeatedly. Our method detects data reuse in the source code of the algorithm to be implemented in hardware, selects and parameterizes data reuse buffers, and generates a register transfer level design of the data buffers and a matching loop controller that coordinates reuse buffers and datapath operations. Throughout this paper, the polyhedral representation is used extensively as it proves to be well suited for calculations on loop nests and data accesses. As a consequence, this paper is limited to affine programs which can be represented in this model. Experiments show that our method outperforms state-of-the-art academic and commercial HLS tools. [ABSTRACT FROM AUTHOR]

In a solar field, the steam production rate and pressure is not constant, but varies and becomes maximum at solar noon. However solar thermal applications such as multi effect desalination with thermo vapour compressor (MED-TVC) system are usually designed for a particular pressure and flow rate. Hence a buffer storage system is needed in solar MED-TVC system to adjust the differences between the steam production and the consumption rates. In the present work steam accumulators were used as buffer storage in direct steam generation (DSG) for correcting the mismatch between production and consumption and also for energy storage. A parametric analysis was performed to investigate the impact of steam accumulator volume and also the irradiance disturbance in solar field on MED-TVC system's performance. This paper presents the transient simulation results of the steam accumulator's output and the corresponding output of the MED-TVC yield from 9:00 h to 20:00 h in a day. [ABSTRACT FROM AUTHOR]

With the rapid progress of mobile Internet, the streaming video service has boom over wireless networks in recent years. A smooth playback experience is crucial for the popularization of these services. However, limited by fluctuating bandwidth and various network impairments, the streaming video inevitably suffers kinds of stalling events, which significantly distorts its temporal structures and results in annoying jerky playback. In this paper, we propose an efficient quality metric to blindly evaluate the user experience for stalled streaming video without using its original sequence. Instead of requiring buffer or manifest information like existing methods, we only access to the decoded video and extract two complementary image features, i.e., global intensity and local texture, to estimate the stall number and duration. Then, by means of a straightforward and easy-to-use linear combination model, we can map the normalized stall number and duration information to a quantitative quality score. Experimental results on the publicly available LIVE-Avvasi mobile video database show that our predicted video quality is highly consistent with the user experience and outperforms many existing quality-of-experience models. [ABSTRACT FROM AUTHOR]

Spatiotemporal proximity analysis to determine spatiotemporal proximal paths is a critical step for many movement analysis methods. However, few effective methods have been developed in the literature for spatiotemporal proximity analysis of movement data. Therefore, this study proposes a space-time-integrated approach for spatiotemporal proximal analysis considering space and time dimensions simultaneously. The proposed approach is based on space-time buffering, which is a natural extension of conventional spatial buffering operation to space and time dimensions. Given a space-time path and spatial tolerance, space-time buffering constructs a space-time region by continuously generating spatial buffers for any location along the space-time path. The constructed space-time region can delimit all space-time locations whose spatial distances to the target trajectory are less than a given tolerance. Five space-time overlapping operations based on this space-time buffering are proposed to retrieve all spatiotemporal proximal trajectories to the target space-time path, in terms of different spatiotemporal proximity metrics of space-time paths, such as Fréchet distance and longest common subsequence. The proposed approach is extended to analyze space-time paths constrained in road networks. The compressed linear reference technique is adopted to implement the proposed approach for spatiotemporal proximity analysis in large movement datasets. A case study using real-world movement data verifies that the proposed approach can efficiently retrieve spatiotemporal proximal paths constrained in road networks from a large movement database, and has significant computational advantage over conventional space-time separated approaches. [ABSTRACT FROM AUTHOR]

Vehicular content networks (VCNs), which distribute medium-volume contents to vehicles in a fully distributed manner, represent the key enabling technology of vehicular infotainment applications. In VCNs, the road-side units (RSUs) cache replicas of contents on the edge of networks to facilitate the timely content delivery to driving-through vehicles when requested. However, due to the limited storage at RSUs and soaring content size for distribution, RSUs can only selectively cache content replicas. The edge caching scheme in RSUs, therefore, becomes a fundamental issue in VCNs. This paper addresses the issue by developing an edge caching scheme in RSUs. Specifically, we first analyze the features of vehicular content requests based on the content access pattern, vehicle's velocity, and road traffic density. A model is then proposed to determine whether and where to obtain the replica of content when the moving vehicle requests it. After this, a cross-entropy-based dynamic content caching scheme is proposed accordingly to cache the contents at the edge of VCNs based on the requests of vehicles and the cooperation among RSUs. Finally, the performance of the proposed scheme is evaluated by extensive simulation experiments. [ABSTRACT FROM AUTHOR]

Delay tolerant networks (DTNs) are an emerging class of wireless networks which enable data delivery even in the absence of end-to-end connectivity. Under these circumstances, message replication may be applied to increase the delivery ratio. The requirement of long term storage and message replication puts a burden on network resources such as buffer and bandwidth. Buffer management is an important issue which greatly affects the performance of routing protocols in DTNs. Two main issues in buffer management are drop decision when buffer overflow occurs and scheduling decision when a transmission opportunity arises. The objective of this paper is to propose an enhancement to the Custom Service Time Scheduling traffic differentiation scheme by integrating it with a fuzzy based buffer ranking mechanism based on three message properties, namely, number of replicas, message size and remaining time-to-live. It uses fuzzy logic to determine outgoing message order and to decide which messages should be discarded within each traffic class queue. Results of simulation study show that the proposed fuzzy logic-based traffic differentiation scheme achieves improved delivery performance over existing traffic differentiation scheme for DTNs. [ABSTRACT FROM AUTHOR]

We study an online buffer management problem under the model introduced by Azar and Gilon (2015) [5] recently. Unit-sized packets arrive and are kept in a First-In-First-Out buffer of size B in an online fashion at a network server. Each packet is associated with an arrival time, a value and a processing cycle time in the buffer. The density of a packet is defined to be the ratio of its value to processing time. It is assumed that every packet can be transmitted only after its processing cycle is completed and only the packet at the head of the buffer can be processed. A packet is allowed to be preempted and then discarded from the buffer. But, the value of a packet is attained only if it is successfully transmitted. Under the model, the objective of online buffer management is to maximize the total value of transmitted packets. This model finds applications to packet scheduling in communication networks. In this study, we consider the model with constant density from a theoretical perspective. We first propose some lower bounds for the problem. Azar and Gilon obtained a 4-competitive algorithm for the online buffer management problem for packets with constant density. Here, we present a ( 2 + 1 B − 1 )-competitive algorithm for the case B > 1 as well as its generalization to the multi-buffer model. Moreover, we prove that the competitive ratio of a deterministic online algorithm is at least four when the buffer size is one. We also conduct experiments to demonstrate the superior performance of the proposed online algorithm against the previous approach. [ABSTRACT FROM AUTHOR]

Session types are behavioural types for guaranteeing that concurrent programs are free from basic communication errors. Recent work has shown that asynchronous session subtyping is undecidable. However, since session types have become popular in mainstream programming languages in which asynchronous communication is the norm rather than the exception, it is crucial to detect significant decidable subtyping relations. Previous work considered extremely restrictive fragments in which limitations were imposed to the size of communication buffer (at most 1) or to the possibility to express multiple choices (disallowing them completely in one of the compared types). In this work, for the first time, we show decidability of a fragment that does not impose any limitation on communication buffers and allows both the compared types to include multiple choices for either input or output, thus yielding a fragment which is more significant from an applicability viewpoint. In general, we study the boundary between decidability and undecidability by considering several fragments of subtyping. Notably, we show that subtyping remains undecidable even if restricted to not using output covariance and input contravariance. [ABSTRACT FROM AUTHOR]

Peer-to-peer (P2P) live streaming systems have gained popularity due to the self-scalability property of the P2P overlay networks. In P2P live streaming, peers retrieve stream content from other peers in the system. Therefore, peer selection strategy is a fundamental element to build an overlay which manages the playback delay and startup delay experienced by the peers. In this paper, we propose a peer selection strategy which manages to build a minimum delay overlay using three different stages of overlay construction. In the first stage, the tracker suggests some peers as prospective partners to a new peer. In the second stage, the peer selects its partners out of these peers such that delay is minimized. The third stage is the topology adaptation phase of peers, where peers reposition themselves in the overlay to maintain minimum delay during peer churn. In the proposed peer selection strategy, peers are selected in all the stages based on parameters such as propagation delay, upload capacity, buffering duration and buffering level. The proposed strategy is compared with two existing strategies in the literature: Fast-Mesh (Ren et al. in IEEE Trans Multimed 11: 1446, 2009) and Hybrid live p2p streaming protocol (Hammami et al., 2014) using simulations. Our results show that playback delay and startup delay are reduced significantly with the help of proposed strategy. We demonstrate that the stability of the system also improves during peer churn. [ABSTRACT FROM AUTHOR]

In this paper, we propose an opportunistic cooperation scheme in a two-user buffer-aided cognitive radio network. In each time slot, the secondary user (SU) will either transmit its own packets, or help the primary user to forward packets, based on a priority factor $\alpha$. According to previous cooperation schemes, some time slots will be wasted if the selected buffer is empty. However, under the proposed scheme, these time slots will be handed over to the nonempty buffer's transmission, which increases the average service rates of buffers at the SU. Considering the bursty nature of sources, we characterize the evolution of buffer states by using the Markov chain. By calculating the probability of time slot handing over, the increased service rates can be theoretically analyzed, so as to the improvements on the stable throughput region and the average end-to-end transmission delay. Moreover, we further discuss the throughput and delay tradeoffs between the two users, which indicates that we can control the traffic load by adjusting the priority factor. Simulations validate our analysis, and reveal that the proposed cooperation scheme with time slot handing over offers a far larger throughput while maintaining a shorter transmission delay compared with previous schemes. [ABSTRACT FROM PUBLISHER]

The impact of a finite relay buffer on the throughput of two-way relay is analyzed from a new queueing theoretic point of view. Distinctively from recent Markov model based analyses, the proposed queueing theoretic analysis is able to infer closed-form asymptotic upper bounds for the throughput, shed valuable insights, and point out limitations in the recent analyses. Validated by simulations, our queueing theoretic analysis reveals that the throughput is increasingly insusceptible to the size of the relay buffer, as the buffer enlarges. Moreover, locking the relay in transmitting xored packets can hardly improve the throughput, especially under balanced channel conditions. This is due to the fact that the relay queues stabilize nonempty, and hence, xored packets are forwarded in most cases. [ABSTRACT FROM PUBLISHER]

Mobile wireless networks have been gaining popularity since the turn of the new millennium as they enable communication to take place without fixed communication infrastructure. This form of communication, which has been made possible by radio links proved its usefulness during emergency medical rescues such as an Ebola pandemic, battlefield communications or other emergency situations, where quick communication is of paramount importance. Nature-inspired algorithms such as AntHocNet, AntSense, among other ant inspired techniques, have been mimicked in solving the communication challenges in wireless networks, but they focus mostly on the ‘next-hop’ in determining routing of data packets from the source to the destination, which tends to suffer from congestion-related problems. Ant routing methods focus more on next-hop neighbours when choosing the shortest path which might have many data packets and are prone to congestion. Focusing on the next-hop neighbours poses a challenge of having other nodes that end up being congested. This problem of routes being heavily used, often decreases throughput rates, leading to the proposed Queuing Ant Colony System (QUACS) which is a bio-inspired, complementing the queuing optimisation approach in routing of data packets across the network. The results of simulations show that QUACS performs better in throughput, packet delivery ratio, end-to-end delay and communication overhead than other ant routing algorithms. This study is particularly beneficial in the ad hoc networks where the QUACS routing method can greatly assist in faster communication and evacuation in emergency for treatment of patients during emergency medical rescue operations. [ABSTRACT FROM AUTHOR]

We consider Persistence , a new online problem concerning optimizing weighted observations in a stream of data when the observer has limited buffer capacity. A stream of weighted items arrive one at a time at the entrance of a buffer with two holding locations. A processor (or observer) can process (observe) an item at the buffer location it chooses, deriving this way the weight of the observed item as profit. The main constraint is that the processor can only move synchronously with the item stream. Persistence is the online problem of scheduling the processor movements through the buffer so that its total derived value is maximized under this constraint. We study the performance of the straight-forward heuristic Threshold , i.e., forcing the processor to “follow” an item through the whole buffer only if its value is above a threshold. We analyze both the optimal offline and Threshold algorithms in the cases where the input stream is either a random permutation, or its items are iid valued. We show that in both cases the competitive ratio achieved by the Threshold algorithm is at least 2/3 when the only statistical knowledge of the items is the median of all possible values. We generalize our results by showing that Threshold, equipped with some minimal statistical advice about the input, achieves competitive ratios in the whole spectrum between 2/3 and 1, following the variation of a newly defined density-like measure of the input. This result is a significant improvement over the case of arbitrary input streams, where we show that no online algorithm can achieve a competitive ratio better than 1/2. [ABSTRACT FROM AUTHOR]

In this paper, design of a real-time video frame buffer with an external memory interface is proposed. In addition, simulation and implementation processes of the design is described. The mentioned system is able to buffer video signals up to 1920×1080 full-HD resolution at 60 Hz frame rate. The memory interface is designed based on an external SDRAM memory and supports burst read/write operations. Input video resolution, video buffer size on memory and burst size of the memory interface are user defined and can be configured. [ABSTRACT FROM AUTHOR]

We propose two cooperative secure transmission schemes to protect a two-hop buffer-aided network assisted by an energy harvesting relay. In the first scheme, we assume that the knowledge of the energy harvesting and fading channels states is known in a non-causal manner (offline). In the second scheme, we assume that this knowledge is known in a causal manner (online). For both schemes, we first design an effective link selection policy by taking into account of the transmission efficiency and information security requirements. We then optimally allocate the harvested power at the relay node. For the offline scheme, we maximize the average secrecy rate under the stability constraints of the data queue and the energy queue according to the proposed link selection policy, and design a two-stage iterative algorithm to select the transmission link and allocate relay’s transmit power. In the online scheme, we first model the average secrecy rate maximum problem as a Markov decision process, and then utilize the causal knowledge to select the best transmission link and optimally allocate relay’s transmit power. In addition, the exact and asymptotic closed-form expressions are derived for the ergodic secrecy rate. Numerical results are presented to validate our analysis and demonstrate that the proposed schemes outperform the other buffered-aided secure transmission schemes assisted by the energy harvesting relay in terms of average secrecy rate. [ABSTRACT FROM PUBLISHER]

Quality of Experience (QoE) of video streaming services has been attracting more and more attention recently. Therefore, in this work we designed and implemented a real-time QoE monitoring system for streaming services with Adaptive Media Playout (AMP), which was implemented into the VideoLAN Client (VLC) media player to dynamically adjust the playout rate of videos according to the buffer fullness of the client buffer. The QoE monitoring system reports the QoE of streaming services in real time so that network/content providers can monitor the qualities of their services and resolve troubles immediately whenever their subscribers encounter them. Several experiments including wired and wireless streaming were conducted to show the effectiveness of the implemented AMP and QoE monitoring system. Experimental results demonstrate that AMP significantly improves the QoE of streaming services according to the Mean Opinion Score (MOS) estimated by our developed program. Additionally, some challenging issues in wireless streaming have been easily identified using the developed QoE monitoring system. [ABSTRACT FROM AUTHOR]

Delay Tolerant Network (DTN) multi-copy routing protocols are privileged to create and transmit multiple copies of each message that causes congestion and some messages are dropped. This process is known as reactive drop because messages were dropped re-actively to overcome buffer overflows. The existing reactive buffer management policies apply a single metric to drop source, relay and destine messages. Hereby, selection to drop a message is dubious because each message as source, relay or destine may have consumed dissimilar magnitude of network resources. Similarly, DTN has included time to live (ttl) parameter which defines lifetime of message. Hence, when ttl expires then message is automatically destroyed from relay nodes. However, time-to-live (ttl) is not applicable on messages reached at their destinations. Moreover, nodes keep replicating messages till ttl expires even-though large number of messages has already been dispersed. In this paper, we have proposed Priority Queue Based Reactive Buffer Management Policy (PQB-R) for DTN under City Based Environments. The PQB-R classifies buffered messages into source, relay and destine queues. Moreover, separate drop metric has been applied on individual queue. The experiment results prove that proposed PQB-R has reduced number of messages transmissions, message drop and increases delivery ratio. [ABSTRACT FROM AUTHOR]

Battery lifetime is a key impediment to long-lasting low power sensor nodes and networks thereof. Energy harvesting-conversion of ambient energy into electrical energy-has emerged as a viable alternative to battery power. Indeed, the harvested energy mitigates the dependency on battery power and can be used to transmit data. However, unfair data delivery delay and energy expenditure among sensors remain important issues for such networks. We study performance of sensor networks with mobile sinks: a mobile sink moves towards the transmission range of the different static sensor nodes to collect their data. We propose and analyse a Markovian queueing system to study the impact of uncertainty in energy harvesting, energy expenditure, data acquisition and data transmission. In particular, the energy harvesting sensor node is described by a system with two queues, one queue corresponding to the battery and the other to the data buffer. We illustrate our approach by numerical examples which show that energy harvesting correlation considerably affects performance measures like the mean data delay and the effective data collection rate. [ABSTRACT FROM AUTHOR]

Modern network elements are increasingly required to deal with heterogeneous traffic. Recent works consider processing policies for buffers that hold packets with different processing requirements (number of processing cycles needed before a packet can be transmitted out) but uniform value, aiming to maximize the throughput, i.e., the number of transmitted packets. Other developments deal with packets of varying value but uniform processing requirement (each packet requires one processing cycle); the objective here is to maximize the total transmitted value. In this paper, we consider a more general problem, combining packets with both nonuniform processing and nonuniform values in the same queue. We study the properties of various processing orders in this setting. We show that in the general case, natural processing policies have poor performance guarantees, with linear lower bounds on their competitive ratio. Moreover, we show several adversarial lower bounds for every priority queue and even for every online policy. On the positive side, in the special case when only two different values are allowed, 1 and V , we present a policy that achieves competitive ratio \left ({1+({W+2}/{V})}\right) , where W$ is the maximal number of required processing cycles. We also consider copying costs during admission. [ABSTRACT FROM AUTHOR]

We consider the reordering buffer problem on a line consisting of n equidistant points. We show that, for any constant δ , an (offline) algorithm that has a buffer ( 1 − δ ) ⋅ k performs worse by a factor of Ω ( log ⁡ n ) than an offline algorithm with buffer k . In particular, this demonstrates that the O ( log ⁡ n ) -competitive online algorithm MovingPartition by Gamzu and Segev (2009) [9] is essentially optimal against any offline algorithm with a slightly larger buffer. [ABSTRACT FROM AUTHOR]

As flash memory becomes popular, flash memory-based solid-state drive (SSD) has been the major storage device. SSD has numerous merits such as high I/O speed, low energy consumption, strong shock resistance and small form factor. Meanwhile, some shortcomings still exist including erase-before-write and different cost for read, write and erase operation. Aiming at efficient buffer management of SSD, this paper proposes a novel approach based on particle swarm optimization (PSO) algorithm. The PSO algorithm is used to estimate the Predict Hot Fitness value of each logical page in the buffer to correctly identify them either as hot or cold by properly reflecting the spatial and temporal locality. The pages predicted as hot are kept in the buffer to maximize the hit ratio and utilization of the SSD buffer. Simulation with real workload shows that the proposed scheme significantly outperforms the representative SSD buffer management schemes in terms of hit ratio and throughput. [ABSTRACT FROM AUTHOR]

Energy harvesting sensor systems typically incorporate energy buffers (e.g., rechargeable batteries and supercapacitors) to accommodate fluctuations in supply. However, the presence of these elements limits the miniaturization of devices. In recent years, researchers have proposed a new paradigm, transient computing, where systems operate directly from the energy harvesting source and allow computation to span across power cycles, without adding energy buffers. Various transient computing approaches have addressed the challenge of power intermittency by retaining the processor's state using non-volatile memory. However, no generic approach has yet been proposed to retain the state of peripherals external to the processing element. This paper proposes RESTOP, flexible middleware which retains the state of multiple external peripherals that are connected to a computing element (i.e., a microcontroller) through protocols such as SPI or I2C. RESTOP acts as an interface between the main application and the peripheral, which keeps a record, at run-time, of the transmitted data in order to restore peripheral configuration after a power interruption. RESTOP is practically implemented and validated using three digitally interfaced peripherals, successfully restoring their configuration after power interruptions, imposing a maximum time overhead of 15% when configuring a peripheral. However, this represents an overhead of only 0.82% during complete execution of our typical sensing application, which is substantially lower than existing approaches. [ABSTRACT FROM AUTHOR]

Keeping the delay experienced by packets while travelling from a source to a destination below certain thresholds is essential to successfully deliver a number of Internet services nowadays. Most of the packet delay can be usually ascribed to the time spent in the many queues encountered by the packet. In this context, the term bufferbloat has been recently coined to denote the uncontrolled growth of the queuing time due, among others, to the excessive size of the buffers and the attitude of TCP to increase the sending rate until a packet is dropped. In this paper, we focus on the queues employed by the traffic control infrastructure and by the network device drivers. Reducing the queuing time due to the former is the objective of a plethora of scheduling algorithms developed in the past years and referred to as Active Queue Management (AQM) algorithms. Conversely, the impact of the additional queuing in the buffer of the network device driver on performance and on the effectiveness of AQM algorithms has instead received much less attention. In this paper, we report the results of an experimental analysis we conducted to gain a better insight into the impact that network device buffers (and their size) have on performance. We also give an in-depth presentation of Dynamic Queue Limits (DQL), an algorithm recently introduced in the Linux kernel to dynamically adapt the size of the buffers held by network device drivers. The experiments we conducted show that DQL not only enables to reduce the queuing time in the network device buffers, which is essential to ensure the effectiveness of AQM algorithms, but also enables to keep latency stable, which is important to reduce the jitter. In order to faithfully reproduce through simulations the dynamics revealed by the experimental study we conducted, we implemented DQL for the popular ns-3 network simulator. In this paper, we describe the design of such implementation and report the results of a simulation study we conducted to show the ability of the simulator to accurately reproduce the experimental results. [ABSTRACT FROM AUTHOR]

Summary As the retransmission mechanism of the Session Initiation Protocol (SIP) significantly increases the amount of incoming traffic and makes an overloaded SIP server unstable, the models created for a stable SIP system cannot be effectively used to evaluate the performance of the overloaded server. To overcome this difficulty, in this paper, we present a fluid-flow model to analyze the priority-based request scheduling mechanism (PRSM) behavior in the overloaded SIP server equipped with an infinite buffer. The PRSM has been proposed in our earlier studies to prevent the overloading of SIP servers, where the original SIP request messages have strict priority over the retransmissions. The performance evaluation of the proposed model for the PRSM and the reference model of the conventional SIP has been reported under various test scenarios. The experiment results of the proposed model verify the effectiveness of the PRSM fluid-flow model as we already demonstrated in our previous studies using our simulation tool. Without loss of generality, the numerical results closely match with the simulation results, indicating that the proposed models can accurately capture the dynamic behavior of a SIP server with the PRSM. [ABSTRACT FROM AUTHOR]

This paper introduces an efficient, low-power, low-area multi-level 2-D discrete Haar wavelet transform (2-D DHWT) architecture. The proposed architecture consists of four add/subtract elements, register bank, three multiplexers and a buffer memory. All or fractions of the N-stage register are used to perform row-column image transposition for every 2-D DHWT decomposition level. A fixed size block memory of $$\frac{{{\varvec{N}}}}{{{\varvec{2}}}}\times \frac{{{\varvec{N}}}}{{{\varvec{2}}}}$$ -sample is used to store low-low frequency band to perform multi-level 2-D DHWT decomposition, except for the first level where no block memory is used. For synthesis results, the proposed architecture outperforms similar architectures in hardware usage, power consumption and speed. Also, it is found that the power delay product of the proposed architecture is less than 1 $$(\hbox {mW} \times \upmu \hbox {s})$$ compared with up to 1.9 $$(\hbox {mW} \times \upmu \hbox {s})$$ for cascaded architecture. Furthermore, an up to 209 MHz processing speed is achieved which enables a three-level 2-D DHWT decomposition of a $$256\times 256$$ -pixel image to be performed within 0.4 ms. [ABSTRACT FROM AUTHOR]

As an emerging novel technology, optical buffering via fiber delay lines (FDLs) is adopted in optical burst switching (OBS) networks for contention resolution. In this paper, we study the blocking probability and the mean delay of an asynchronous single-wavelength optical buffer, where the burst arrival process is Poisson and burst-length distribution is general. With the aid of Level Crossing (LC) method, we first derive the integral equations to model the dynamics of the buffer. We then propose a method to solve these equations. Finally we present the mathematical expressions of blocking probabilities and the mean delays for the optical buffer with general burst size distribution. Numerical examples are provided to validate our results, and some interesting observations from the numerical examples are highlighted. [ABSTRACT FROM AUTHOR]

Double buffering is an effective mechanism to hide the latency of data transfers between on-chip and off-chip memory. However, in dataflow architecture, the swapping of two buffers during the execution of many tiles decreases the performance because of repetitive filling and draining of the dataflow accelerator. In this work, we propose a non-stop double buffering mechanism for dataflow architecture. The proposed non-stop mechanism assigns tiles to the processing element array without stopping the execution of processing elements through optimizing control logic in dataflow architecture. Moreover, we propose a work-flow program to cooperate with the non-stop double buffering mechanism. After optimizations both on control logic and on work-flow program, the filling and draining of the array needs to be done only once across the execution of all tiles belonging to the same dataflow graph. Experimental results show that the proposed double buffering mechanism for dataflow architecture achieves a 16.2% average efficiency improvement over that without the optimization. [ABSTRACT FROM AUTHOR]

We propose a low area overhead and power-efficient asynchronous-logic quasi-delay-insensitive (QDI) sense-amplifier half-buffer (SAHB) approach with quad-rail (i.e., 1-of-4) data encoding. The proposed quad-rail SAHB approach is targeted for area- and energy-efficient asynchronous network-on-chip (ANoC) router designs. There are three main features in the proposed quad-rail SAHB approach. First, the quad-rail SAHB is designed to use four wires for selecting four ANoC router directions, hence reducing the number of transistors and area overhead. Second, the quad-rail SAHB switches only one out of four wires for 2-bit data propagation, hence reducing the number of transistor switchings and dynamic power dissipation. Third, the quad-rail SAHB abides by QDI rules, hence the designed ANoC router features high operational robustness toward process-voltage-temperature (PVT) variations. Based on the 65-nm CMOS process, we use the proposed quad-rail SAHB to implement and prototype an 18-bit ANoC router design. When benchmarked against the dual-rail counterpart, the proposed quad-rail SAHB ANoC router features 32% smaller area and dissipates 50% lower energy under the same excellent operational robustness toward PVT variations. When compared to the other reported ANoC routers, our proposed quad-rail SAHB ANoC router is one of the high operational robustness, smallest area, and most energy-efficient designs. [ABSTRACT FROM PUBLISHER]

We propose a suppressive fair buffer management policy for intermittently connected mobile ad-hoc networks. So far, several buffer management policies have been considered. These existing buffer management policies assume that all stored messages can be replaced when nodes encounter each other. Buffer management policies, however, can prioritize messages stored at the receiving side over those at the sending side. By doing this, message transmissions are suppressive, and thus energy consumption in terms of sending messages is reduced. Moreover, our proposed policy gives relay messages with a small number of message copies to high priority. Specifically, our proposed policy maintains a sharing of buffer spaces that is as fair as possible. In this paper, we reveal how the suppression of receiving messages affects the system performance compared with existing buffer management policies. Through simulation experiments, we show that the suppressive fair buffer management policy improves energy consumption without largely degrading the delivery failure probability and the mean delivery delay. [ABSTRACT FROM AUTHOR]

Buffer overflow vulnerability is a kind of consequence in which programmers’ intentions are not implemented correctly. In this paper, a static analysis method based on machine learning is proposed to assist in auditing buffer overflow vulnerabilities. First, an extended code property graph is constructed from the source code to extract seven kinds of static attributes, which are used to describe buffer properties. After embedding these attributes into a vector space, five frequently used machine learning algorithms are employed to classify the functions into suspicious vulnerable functions and secure ones. The five classifiers reached an average recall of 83.5%, average true negative rate of 85.9%, a best recall of 96.6%, and a best true negative rate of 91.4%. Due to the imbalance of the training samples, the average precision of the classifiers is 68.9% and the average F1 score is 75.2%. When the classifiers were applied to a new program, our method could reduce the false positive to 1/12 compared to Flawfinder. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the cross-layer optimization of caching and fast video delivery for enhanced video streaming quality of experience in two-hop relaying networks, where a base station supplies video data to multiple users with the help of relays. Different from conventional systems, each half-duplex relay node is equipped with a cache and a buffer to facilitate joint scheduling of video fetching and delivery. This introduces channel diversity gains and facilitates fast video delivery. In particular, we investigate two-stage caching and delivery control schemes for the minimization of the overall video delivery time. An offline caching and delivery optimization problem, which assumes full knowledge of user requests and channel state information (CSI), is formulated but turns out to be functional and nonconvex. However, we unveil a hidden quasi-convexity and convexity in the two layers of the decomposed problem and, hence, solve the offline problem optimally and efficiently. Moreover, online video delivery control exploiting statistical CSI is investigated under a stochastic dynamic programming (DP) framework. To mitigate the high computational complexity of DP, we further propose a low-complexity online video delivery algorithm, which achieves close-to-optimal performance in the high buffer capacity regime. Simulation results show that our offline and online schemes can significantly reduce the overall video delivery time due to the degrees of freedom enabled by caching and buffering. Besides, an interesting tradeoff between caching and buffering gains in exploiting the diversity of the wireless channel is revealed. [ABSTRACT FROM AUTHOR]

An optical overlaid star network is a class of agile all-photonic networks that consists of one or more core node(s) at the center of the star network and a number of edge nodes around the core node. In this architecture, a core node may use a scheduling algorithm for transmission of traffic through the network. A core node is responsible for scheduling optical packets that arrive from edge nodes and switching them toward their destinations. Nowadays, most edge nodes use virtual output queue (VOQ) architecture for buffering client packets to achieve high throughput. This paper presents two efficient scheduling algorithms called discretionary iterative matching (DIM) and adaptive DIM. These schedulers find maximum matching in a small number of iterations and provide high throughput and incur low delay. The number of arbiters in these schedulers and the number of messages exchanged between inputs and outputs of a core node are reduced. We show that DIM and adaptive DIM can provide better performance in comparison with iterative roundrobin matching with SLIP (iSLIP). SLIP means the act of sliding for a short distance to select one of the requested connections based on the scheduling algorithm. [ABSTRACT FROM AUTHOR]

MapReduce is a popular computing model for parallel data processing on large-scale datasets, which can vary from gigabytes to terabytes and petabytes. Though Hadoop MapReduce normally uses Hadoop Distributed File System (HDFS) local file system, it can be configured to use a remote file system. Then, an interesting question is raised: for a given application, which is the best running platform among the different combinations of scale-up and scale-out Hadoop with remote and local file systems. However, there has been no previous research on how different types of applications (e.g., CPU-intensive, data-intensive) with different characteristics (e.g., input data size) can benefit from the different platforms. Thus, in this paper, we conduct a comprehensive performance measurement of different applications on scale-up and scale-out clusters configured with HDFS and a remote file system (i.e., OFS), respectively. We identify and study how different job characteristics (e.g., input data size, the number of file reads/writes, and the amount of computations) affect the performance of different applications on the different platforms. Based on the measurement results, we also propose a performance prediction model to help users select the best platforms that lead to the minimum latency. Our evaluation using a Facebook workload trace demonstrates the effectiveness of our prediction model. This study is expected to provide a guidance for users to choose the best platform to run different applications with different characteristics in the environment that provides both remote and local storage, such as HPC cluster and cloud environment. [ABSTRACT FROM PUBLISHER]

Stream processing is a special form of the dataflow execution model that offers extensive opportunities for optimization and automatic parallelism. A streaming application is represented by a graph of computation stages that communicate with each other via FIFO channels. In shared-memory environment, an FIFO channel is classically a common, fixed-size synchronized buffer shared between the producer and the consumer. As the number of concurrent stage workers increases, the synchronization overheads, such as contention and waiting times, rise sharply and severely impair application performance. In this paper, we present a novel multithreaded model which isolates memory between threads by default and provides a higher level abstraction for scalable unicast or multicast communication between threads - CHAUS (Channel for Unbounded Streaming). The CHAUS model hides the underlying synchronization details, but requires the user to declare producer-consumer relationship of a channel in advance. It is the duty of the runtime system to ensure reliable data transmission at data item granularity as declared. To achieve unbounded buffer for streaming and reduce the synchronization overheads, we propose a virtual memory based solution to implement a scalable CHAUS channel. We check the programmability of CHAUS by successfully porting dedup and ferret from PARSEC as well as implementing MapReduce library with Phoenix-like API. The experimental results show that workloads built with CHAUS run faster than those with Pthreads, and CHAUS has the best scalability compared with two Pthread versions. There are three workloads whose CHAUS versions only spend no more than 0.17x runtime of Pthreads on both 16 and 32 cores. [ABSTRACT FROM AUTHOR]

To design the write buffer and flash translation layer (FTL) for a solid-state drive (SSD), previous studies have tried to increase overall SSD performance by parallel I/O and garbage collection overhead reduction. Recent works have proposed pattern-based managements, which uses the request size and read- or writeintensiveness to apply different policies to each type of data. In our observation, the locations of read and write requests are closely related, and the pattern of each type of data can be changed. In thiswork, we propose SUPA, a single unified read-write buffer and pattern-change-aware FTL on multi-channel SSD architecture. To increase both read and write hit ratios on the buffer based on locality, we use a single unified read-write buffer for both clean and dirty blocks. With proposed buffer, we can increase buffer hit ratio up to 8.0% and reduce 33.6% and 7.5% of read and write latencies, respectively. To handle pattern-changed blocks, we add a pattern handler between the buffer and the FTL, which monitors channel status and handles data by applying one of the two different policies according to the pattern changes. With pattern change handling process, we can reduce 1.0% and 15.4% of read and write latencies, respectively. In total, our evaluations show that SUPA can get up to 2.0 and 3.9 times less read and write latency, respectively, without loss of lifetime in comparison to previous works. [ABSTRACT FROM AUTHOR]

This paper considers a two-machine continuous flow manufacturing system with a buffer of finite capacity, and where the machines are subjected to failures, minimal repairs, and condition-based preventive maintenance. Each machine can degrade into several discrete states, which are characterized by different performance parameters, ranging from perfect functioning to complete shutdown. When a specified degraded state is exited, a preventive maintenance action is performed to restore the machine to one of the higher performance states. We evaluate the impact of preventive maintenance strategies for each machine, in order to determine their impact on production rate and total cost. A methodology is developed to analyze the complex trade-off between the contributions of preventive maintenance and of the buffer to the system performance. It is shown that preventive maintenance should be scheduled not to optimize the performance for each machine individually; its scheduling is best considered from the perspective of the manufacturing system as a whole. The analysis also reveals the importance of considering machine speeds when optimizing the choice of maintenance policy. [ABSTRACT FROM AUTHOR]

Understanding the real achievable performance of mobile ad hoc networks (MANETs) under practical network constraints is of great importance for their applications in future highly heterogeneous wireless network environments. This paper explores, for the first time, the performance modeling for MANETs under a general limited buffer constraint, where each network node maintains a limited source buffer of size $B_s$ to store its locally generated packets and also a limited shared relay buffer of size $B_r$ to store relay packets for other nodes. Based on the Queuing theory and birth-death chain theory, we first develop a general theoretical framework to fully depict the source/relay buffer occupancy process in such a MANET, which applies to any distributed MAC protocol and any mobility model that leads to the uniform distribution of nodes’ locations in steady state. With the help of this framework, we then derive the exact expressions of several key network performance metrics, including achievable throughput, throughput capacity, and expected end-to-end delay. We further conduct case studies under two network scenarios and provide the corresponding theoretical/simulation results to demonstrate the application as well as the efficiency of our theoretical framework. Finally, we present extensive numerical results to illustrate the impacts of buffer constraint on the performance of a buffer-limited MANET. [ABSTRACT FROM PUBLISHER]