Recent open source wireless sensor network supporting simulators: A performance comparison

Any common methodology for functionality research in the field of communication systems engineering is network simulation. There is always the overriding worry when utilizing simulation that the results may not reflect appropriate behavior. Therefore, it is important to recognize the particular strengths and also flaws of such simulators. There are a variety of network simulators, as an illustration, NS-2, NS-3, OMNET++, SWAN, OPNET, Jist, and also GloMoSiM and so forth.

As a result, the selection of any network simulator for assessing investigation function is really a critical activity for researchers. The leading emphasis in this research is usually to examine the particular advanced, open source network simulators based on the parameters, CPU usage, memory usage, computational time period, and also scalibility by simulating a wireless sensor network routing protocol, to identify a best network simulator to the investigation area.

Programmable firewall using Software Defined Networking

Software Defined Networking is an exciting technology that enables innovation and flexibility in designing and managing networks, but it also introduces new security issues. Our Major challenge is to build powerful and flexible firewall applications for protecting software defined based networks. In this paper we focus on designing and developing OpenFlow based firewall application.

The implementation shows that most of the firewall functionalities can be built using software, without need of dedicated hardware. We are using open source POX Controller based on python for our experiments. To perform experiment, we have used VMPlayer virtualization solution and installed Mininet emulator for creating network topologies. In this paper, we present the implementation details as well as experimentation results of firewall application.

SNNAP: Approximate computing on programmable SoCs via neural acceleration

Many applications that can take advantage of accelerators are amenable to approximate execution. Past work has shown that neural acceleration is a viable way to accelerate approximate code. In light of the growing availability of on-chip field-programmable gate arrays (FPGAs), this paper explores neural acceleration on off-the-shelf programmable SoCs. We describe the design and implementation of SNNAP, a flexible FPGA-based neural accelerator for approximate programs. SNNAP is designed to work with a compiler workflow that configures the neural network’s topology and weights instead of the programmable logic of the FPGA itself. This approach enables effective use of neural acceleration in commercially available devices and accelerates different applications without costly FPGA reconfigurations.

No hardware expertise is required to accelerate software with SNNAP, so the effort required can be substantially lower than custom hardware design for an FPGA fabric and possibly even lower than current “C-to-gates” high-level synthesis (HLS) tools. Our measurements on a Xilinx Zynq FPGA show that SNNAP yields a geometric mean of 3.8× speedup (as high as 38.1×) and 2.8× energy savings (as high as 28 x) with less than 10% quality loss across all applications but one. We also compare SNNAP with designs generated by commercial HLS tools and show that SNNAP has similar performance overall, with better resource-normalized throughput on 4 out of 7 benchmarks.

A new bandwidth-efficient multicast routing scheme for mobile Ad hoc Networks

This paper proposes an improved scheme based on Bandwidth-Efficient Multicast Routing (BEMR) for Mobile Ad Hoc Networks (MANET) to further reduce the control overhead whilst increasing the overall bandwidth efficiency. After carefully studying the original BEMR design, L· new approaches are proposed to enhance the BEMR performance One is in the tree set-up phase, while the other is for broken link recovery.

Both the original BEMR and the new scheme (IBEMR) are simulated in self-developed OPNET-based platform. The IBEMR scheme eventually builds a shared tree for this multicast group rather than a dedicate tree for a particular multicast sender generated by original BEMR. The result shows that for both route setup phase and route recovery phase, the IBEMR scheme provides better multicast efficiency with further reduced communication overhead.

Assessing the impact of resource attack in Software Defined Network

Software Defined Network (SDN) empowers network operators with more flexibility to program their networks. In SDN, dummy switches on the data plane dynamically forward packets based on the rules which are managed by a centralized controller. To apply the rules, switches need to write the rules in its flow table. However, because the size of the flow table is limited, a scalability problem can be an issue. Also, this scalability problem becomes a security issue related to Distributed Denial of Service (DDoS) attacks, especially the resource attack which consumes all flow tables of switches.

In this paper, we explore the impact of the resource attack to a SDN network. The resource attack is emulated on the SDN with mininet and OpenDaylight, and the effect of resource attack to the SDN is deeply analyzed in the aspects of delay and bandwidth. Through the evaluation, we highlight the importance of managing the flow tables with the awareness of their size limitation. Also, we discuss solutions which can address the resource attack and their challenges.

Recent trends in multicarrier underwater acoustic communications

Underwater acoustic communication is essential in applications like remote control in the offshore oil industry, pollution monitoring in environmental systems, collection of scientific data recorded at ocean-bottom stations, disaster detection and early warning and underwater surveillance. Research on underwater wireless communication techniques plays a vital role in further exploring oceans and other marine environments. There has been an extensive growth in the volume of literature for underwater acoustic (UWA) communication but still it remains to be one of the most challenging areas of wirelesscommunication.

Over the years attention has turned on applying modified versions of multicarrier (MC)communication to underwater channel. This paper reviews the recent developments in the area of UWAcommunication related to multicarrier communication and particularly to orthogonal frequency division multiplexing (OFDM) with respect to applied, theoretical and simulation studies. An attempt has been made to present a compact yet exhaustive literature survey that will serve as a standard reference for researchers working in the area. Stress has been laid on the physical layer issues as it works as the basic foundation of any network. The focus areas of research activities have been identified and a summary of the ongoing activities and future trends has been presented.

An Information-Centric Communication Infrastructure for Real-Time State Estimation of Active Distribution Networks

The evolution toward emerging active distribution networks (ADNs) can be realized via a real-time state estimation (RTSE) application facilitated by the use of phasor measurement units (PMUs). A critical challenge in deploying PMU-based RTSE applications at large scale is the lack of a scalable and flexible communication infrastructure for the timely (i.e., sub-second) delivery of the high volume of synchronized and continuous synchrophasor measurements. We address this challenge by introducing a communication platform called C-DAX based on the information-centric networking (ICN) concept. With a topic-based publish-subscribe engine that decouples data producers and consumers in time and space, C-DAX enables efficient synchrophasor measurement delivery, as well as flexible and scalable (re)configuration of PMU data communication for seamless full observability of power conditions in complex and dynamic scenarios. Based on the derived set of requirements for supporting PMU-based RTSE in ADNs, we design the ICN-based C-DAX communication platform, together with a joint optimized physical network resource provisioning strategy, in order to enable the agile PMU datacommunications in near real-time.

In this paper, C-DAX is validated via a field trial implementation deployed over a sample feeder in a real-distribution network; it is also evaluated through simulation-based experiments using a large set of real medium voltage grid topologies currently operating live in The Netherlands. This is the first work that applies emerging communication paradigms, such as ICN, to smart grids while maintaining the required hard real-time data delivery as demonstrated through field trials at national scale. As such, it aims to become a blueprint for the application of ICN-based general purpose communication platforms to ADNs.

Social Skills?: There?s an app for that

No, really, there is. The iPad app store features about a dozen applications designed to help children on the autism spectrum develop everyday social skills such as recognizing facial expressions, reading body language, and initiating conversations. Because these applications are relatively new, there’s more hype than evidence regarding their effectiveness, but parents and autism researchers are understandably hopeful that this new technology will enable these kids to navigate more easily through our socially demanding world.

But, like a drug that has the opposite effect when ingested by the wrong person, addictive reliance on technology is causing a debilitating decline in social skills in the vast majority of our younger population.

There is a Will, There is a Way: A New Mechanism for Traffic Control Based on VTL and VANET

Traffic light is regarded as one of the most effective ways to alleviate traffic congestion and carbon emission problems. However, traditional traffic light cannot meet the challenges in traffic regulation posed by the fast growing number of vehicles and increasing complexity of road conditions. In this paper, we propose a dynamic traffic regulation method based on virtual traffic light (VTL) for Vehicle Ad Hoc Network (VANET).

In our framework, each vehicle can express its “will” – the desire of moving forward – and share among one another its “will” – value and related traffic information at a traffic light controlled intersection. Based on the traffic information collected in real time, the virtual traffic light in our scheme can be adaptive to the changing environment. We conducted a number of simulation experiments with different scenarios using network simulator NS3 combined with traffic simulator SUMO. The results demonstrate the viability of our solution in reducing waiting time and improving the traffic efficiency.

Empirical rapid and accurate prediction model for data mining tasks in cloud computing environments

With the arrival of big data and cloud computing as a computing concept, it is becoming ever more critical to efficiently choose the most optimum machine on which to execute a program, for example in the healthcare environment. This process of choice is also complicated by the fact that numerous machines are available as virtual machines. Hence, predicting the most optimum choice of machine based on a target application is a challenge. Prediction techniques consume large amount of computing resources when operating with multi-dimensional data that can cause long delays compounded by cross validation process in evaluating and choosing the most optimum prediction model.

We propose a model of prediction techniques to predict and classify some of the health datasets to retrieve useful knowledge to illustrate how a data miner can choose a suitable machine especially in cloud environment with good accuracy in a timely manner. Our results show that the execution time has an inverse relation with the use of resources of a machine and the accuracy of prediction could be different from one machine to another using the same predicting technique and dataset.