Design and Evaluation of Bulk Data Transfer Extensions for the NFComms Framework

With the fast proliferation of cloud computing, major cloud service providers, e.g., Amazon, Google, Facebook, etc., have been deploying more and more geographically distributed data centers to provide customers with better reliability and quality of services. A basic demand in such a geo-distributed data center system is to transfer bulk volumes of data from one data center to another. Geographic distribution and large delay-tolerance of such inter-data-center bulk data transfers provide cloud service providers opportunities to optimize the operating cost. Most existing studies on inter-data-center bulk data transfers focus on minimizing the network bandwidth cost. However, the energy-cost of the bulk data transfers, which also accounts for a large proportion of operating cost in the data centers, still remains unexplored. This is an important problem, especially in the multi-electricity-market environment, where the electricity price exhibits both spatial and temporal diversities. In this paper, we systematically study the problem of how to route and schedule inter-data-center bulk data transfers to minimize the energy-cost for geo-distributed data centers. We model this problem as a min-cost multi-commodity flow problem and develop an efficient two-stage optimization method to solve it. Extensive evaluations with real-life inter-data-center network and electricity prices show that our method brings significant energy-cost savings over existing bulk data transfer methods.

The different types of messages used by a parallel application program executing in a distributed system can each have unique characteristics so that no single communication network can produce the lowest latency for all messages. For instance, short control messages may be sent with the lowest overhead on one type of network, such as Ethernet, while bulk data transfers may be better suited to a different type of network, such as Fibre Channel or HiPPI. In this paper, we investigate how to exploit multiple heterogeneous communication networks that interconnect the same set of processing nodes by dynamically selecting the best (lowest latency) network for each message based on the message size. We also show how to aggregate these multiple parallel networks into a single virtual network to further reduce the latency and increase the available bandwidth. We test this multiplexing and aggregation on a cluster of SGI multiprocessors interconnected with both Fibre Channel and Ethernet. We find that multiplexing between Ethernet and Fibre Channel can substantially reduce communication overhead in a synthetic benchmark compared to using either network alone. Aggregating these two networks into a single virtual network can further reduce communication delays for applications with many large messages. The best choice of either multiplexing or aggregation depends on the mix of message sizes in application program and the relative overheads of the two networks.

Building on Selex ES's unique experience in this domain, the Miysis DIRCM System is the culmination of over nine years of extensive development, test, validation and certification, resulting in a twin-head, spherical coverage DIRCM system that is less than 40kg and is capable of protecting the full range of platform types from the smallest helicopters to the largest transport aircraft. This paper discusses some of the benefits that have been achieved from the application of advanced EO technology to the Miysis DIRCM System, and also considers some of the system trades a designer may have to undertake, including some implications more advanced seeker designs may have on EO/IRCM system design and architecture. The extensive test and evaluation that was undertaken at every stage of the programme, including simulation, laboratory testing, platform and target dynamic testing in a System Integration Laboratory (SIL), flight trial, missile live-fire, environmental testing and reliability testing, all of which was required in order to ensure that the system provides the requisite levels of protection against the latest, sophisticated all-aspect IR MANPADS is also covered. Finally, the approach necessary to ensure that the equipment is suited to all air platforms from the smallest helicopters to large transports, while also ensuring that it achieves an inherent high reliability and an ease of manufacture and repair such that a step change in through-life cost in comparison to previous generation systems can be achieved is described.

We present Machete, a straightforward segmenter one can use to isolate custom gestures in continuous input. Machete uses traditional continuous dynamic programming with a novel dissimilarity measure to align incoming data with gesture class templates in real time. Advantages of Machete over alternative techniques is that our segmenter is computationally efficient, accurate, device-agnostic, and works with a single training sample. We demonstrate Machete’s effectiveness through an extensive evaluation using four new high-activity datasets that combine puppeteering, direct manipulation, and gestures. We find that Machete outperforms three alternative techniques in segmentation accuracy and latency, making Machete the most performant segmenter. We further show that when combined with a custom gesture recognizer, Machete is the only option that achieves both high recognition accuracy and low latency in a video game application.

Existing Web services rely on HTTP and TCP as the underlying transport protocols for SOAP messaging. While these protocols provide a number of benefits, including being able to pass through firewalls and are universally supported across different platforms, they were designed for wired networks with high bandwidth, low latency and low error rate transmissions. Due to the variability of wireless channels however, these assumptions do not hold in wireless environments. In this paper, we investigate the performance of HTTP and TCP as transport protocols for SOAP in wireless environments. Through extensive testing, we show that SOAP-over-HTTP and SOAP-over-TCP are inefficient and lead to high latency and transmission overhead for wireless applications. To overcome these limitations, we study the use of UDP as a binding protocol for SOAP. The results obtained are promising and show that SOAP-over-UDP provides throughput that is ten times higher compared to SOAP-over-HTTP in a wireless setting. Furthermore, using UDP to transport SOAP messages reduces transmission overhead by more than 50% compared to SOAP-over-HTTP. Finally, to illustrate where UDP binding can be useful, example applications are also described in this paper

DIMMnet-2 is a network interface for PC cluster, plugged into a DIMM slot. Connecting network interface into commonly used memory bus reduces the cost of building PC cluster compared with using expensive machines with recent high performance I/O bus like PCIX. Moreover, low latency communication from the host CPU can be achieved. In this paper, implementation of the mechanisms for low latency communication on the DIMMnet-2 prototype board by making the best use of the memory slot is shown. Its latency for 4 Bytes data transfer is only 1.4 µs which is lower than those of InfiniBand and QsNET II on condition those host processes are Intel Xeon.

In this article, we suggest a mechanism to ease privacy management in social networks. This mechanism is based on a relationship model which renders the asymmetry and the diversity of real-life relationships between peers. This model defines attributes that are used in an attribute-based encryption system which protects both user information and exchanged data within the social network. This project is currently a work in progress and the ideas developed here will be confirmed during an extensive implementation and testing phase.

Early disruption of Advanced Persistent Threat (APT) campaigns hinges on recognising the attackers' tactics, techniques and procedures (TTPs), which remain stable even after individual indicators of compromise (IOC) are rotated. Most prior studies derive such patterns from vendor-curated cyber-threat-intelligence reports, sources that can reflect commercial or geopolitical bias. To reduce this bias, a corpus of 2,097 malware samples confidently attributed to ten established APT groups was assembled, and every sample was detonated in a high-fidelity sandbox. The sandbox generates lengthy, unstructured text traces that capture both static artefacts and dynamic behaviour. The contributions are fourfold: this bias-reduced malware-TTP corpus is published, LTDCT-TTPDBIO is introduced to turn raw sandbox logs into precise ATT&CK labels with low latency, and an extensive comparative evaluation is provided that links TTP prevalence to APT groups' capabilities. These raw traces are then processed by LTDCT-TTPDBIO, a latent-topic model tuned with a Birch-inspired optimiser and paired with a random-forest classifier, which converts them into precise MITRE ATT&CK labels in about 1.45min per sample. This latency is roughly 4.5 times shorter than the fastest baseline and six to eight times shorter than recent transformer- and graph-based approaches, yet the model still delivers the best detection quality. With an 80-20 train-test split, it reaches an accuracy of 95.33%, a precision of 97.32%, a recall of 94.61% and an F1-score of 95.65%; with a 70-30 split, the F1-score climbs to 95.78%. These figures outperform the eight baseline algorithms evaluated in this study, with the highest F1-score among them being 93.38%. The resulting structured behaviour ground-truth dataset quantifies how malware and tactics are distributed across the ten APT groups. It pinpoints the most frequently observed techniques together with their defensive implications. Efficient extraction of TTPs from raw sandbox text therefore offers a durable and bias-resistant foundation for proactive APT defence.

As an extension of cloud computing, fog computing at the edge of networks provides low latency, location awareness, and real-time interactions. At the same time, millimeter wave (mmWave) communications are able to provide directional multi-gigabit transmission rates with large available bandwidth. Based on the user mobile trajectories in a region, several activity hotspots that users pass by frequently can be obtained. By caching popular content at the edge nodes near the hotspots, users can download the cached content directly at a short distance, and the user experience can be significantly improved. Considering multiple hotspots in a region, how to efficiently schedule the transmission for the caching at edge nodes becomes a key problem. In this paper, we focus on the problem of mobility aware transmission scheduling for caching at edge nodes near hotspots, and utilize multi-hop relaying and concurrent transmissions to achieve better performance. After formulating the optimal scheduling problem as a stochastic nonlinear mixed integer program, we propose a mobility aware caching scheduling scheme, called MHRC (Multi-Hop Relaying based Caching), where multi-hop D2D paths are established for edge nodes, and concurrent transmissions are exploited in the scheduling of caching at edge nodes. Extensive performance evaluation demonstrates MHRC achieves more than 1x higher expected cached data amount compared with state-of-the-art schemes.

Several manufacturers have already started to commercialize near-bank Processing-In-Memory (PIM) architectures, after decades of research efforts. Near-bank PIM architectures place simple cores close to DRAM banks. Recent research demonstrates that they can yield significant performance and energy improvements in parallel applications by alleviating data access costs. Real PIM systems can provide high levels of parallelism, large aggregate memory bandwidth and low memory access latency, thereby being a good fit to accelerate the Sparse Matrix Vector Multiplication (SpMV) kernel. SpMV has been characterized as one of the most significant and thoroughly studied scientific computation kernels. It is primarily a memory-bound kernel with intensive memory accesses due its algorithmic nature, the compressed matrix format used, and the sparsity patterns of the input matrices given. This paper provides the first comprehensive analysis of SpMV on a real-world PIM architecture, and presents SparseP, the first SpMV library for real PIM architectures. We make two key contributions. First, we design efficient SpMV algorithms to accelerate the SpMV kernel in current and future PIM systems, while covering a wide variety of sparse matrices with diverse sparsity patterns. Second, we provide the first comprehensive analysis of SpMV on a real PIM architecture. Specifically, we conduct our rigorous experimental analysis of SpMV kernels in the UPMEM PIM system, the first publicly-available real-world PIM architecture. Our extensive evaluation provides new insights and recommendations for software designers and hardware architects to efficiently accelerate the SpMV kernel on real PIM systems. For more information about our thorough characterization on the SpMV PIM execution, results, insights and the open-source SparseP software package [21], we refer the reader to the full version of the paper [3, 4]. The SparseP software package is publicly and freely available at https://github.com/CMU-SAFARI/SparseP.

This study aims to analyze the performance of agricultural extension workers in rice field agricultural extension in Baruga Village, Baruga District, Kendari City. The study population consists of 280 active rice farmers participating in agricultural extension programs. The sample size is 28 farmers (10% of the population), selected using simple random sampling. Data analysis employs descriptive statistics to describe the state of the study variables. The results of the study indicate that the performance of agricultural extension officers in rice farming extension in the Amohalo area in Baruga Village, Baruga District, Kendari City, is in the moderate category. Agricultural extension officers in Baruga Village, Baruga District, Kendari City, have demonstrated adequate or moderate performance in the preparation, implementation, and evaluation of rice farming extension.

RISC-V is a modern open source Instruction Set Architecture (ISA) and designed in a very extendable manner, which allows for highly application specific solutions. However, the identification of suitable instruction set extensions usually requires a significant manual effort and therefore is a very challenging process. In this paper we propose a lightweight alternative methodology to find suitable application-specific RISC-V extensions, using a Virtual Prototype (VP). This is done, purely by observing the used instructions during the execution of the targeted application on the VP. Therefore, no further information about the application itself are needed. In this context the advantages and the flexibility of a VP and the straightforward extendability of the RISC-V ISA are demonstrated.

Network interfaces for programmable NICs and multicore platforms

A novel prediction of remaining useful life time of rolling bearings using convolutional neural network with bidirectional long short term memory

Virtualisation of experiments is one of the most efficient ways for the modernisation of traditional engineering laboratories. In that context, remote triggering, or remotely controlling actual physical laboratory hardware, is one of the best ways to do this. This paper provides the framework and methodology behind the creation of a Remote Triggered Solar Thermal Energy Parabolic Trough experiment. The `Remote Trigger Solar Thermal Energy Parabolic Trough Lab', is a virtual experiment for analysing the heating capacity of a parabolic trough collector over different flow rates of the heat transfer fluid and for different angles of incidence of radiation. The experiment has a web interface in which the student can view and control the actual hardware device, changing the various parameters which affect the efficiency of the parabolic trough. These parameters can be measured and displayed on the Web interface in a spreadsheet and are plotted in a novel and learning-effective manner. This experiment is being hosted on our VLCAP (Virtual Labs Collaboration and Accessibility Platform) [1] and extensive testing and evaluation is underway. It will be open for a large number of students from all over the world to use the site. This paper presents the implementation strategies and methods used which have proven effective for Virtual Labs, along with a technical description of the experiment and the system used to create and host the experiment.