About NS3 Simulation Projects

Traditionally, distribution network monitoring has been focused on primary substations (i.e., high voltage/medium voltage level), whereas low voltage (LV) network has not been monitored at all. With rapid growth and penetration of distributed energy resources in LV grids, there is growing interest in extending the real-time monitoring to LV level. The framework program FP7 European Project INTEGRIS proposes an integrated real-time LV network monitoring solution and implements it in a cost-efficient way.

This solution integrates smart metering data with secondary substation measurements to get a more accurate and real-time view about LV grid, uses “decentralized” distribution management architecture to optimize data flow, and uses International Electrotechnical Commission 61850 Standard-based interfaces to improve interoperability. This paper focuses on information and communications technology perspective, explains the implementation details of this monitoring solution, and presents its functionality/performance testing results from two distribution system operator field trials and from real-time digital simulator laboratory.

This paper, the second of the series on developing a LiFePO₄ (LFP) battery discharge simulator for EV applications, presents an approach for developing the battery simulator. After the optimal battery model was established, in the first paper, the main drawbacks of battery simulator are addressed and a new strategy is proposed.

This strategy uses neural networks (NN) for online estimation of the battery parameters during discharge. The proposed simulator is validated by comparisons with a typicalsimulator and data from a LFP battery submitted to discharge profile in concordance with a driving cycle.

This paper presents therm, an integrated framework for cycle-accurate thermal and functional evaluation of systems-on-chip. The presented framework enables accurate characterization of thermal behaviour by generating detailed physical models for components based on input specifications, and simulating them within a tightly integrated co-simulation platform with an embedded thermal simulator.

Therm’s fine-grained modelling approach yields 70% higher accuracy in hotspot resolution as compared to conventional approaches that abstract component internals. Simulation runtime time is reduced by up to 36% over conventional continuous approaches through the use of thermal check pointing, enabling the fast-forwarding of thermal simulations without loss of thermal continuity.

Cost estimation is crucial in the performance modeling of parallel algorithms and allocation of computational resources on distributed systems. This paper presents a novel methodology for estimating the cost of constrained producer-consumer (CPC) algorithms. In CPC algorithms, the computation is performed by classes of nodes (tasks), separated in time. The methodology combines data flow analysis with communication latencies to determine the production and consumption of data on different processors, which helps in determining the amount of computations and communication. The cost metric that we develop in this paper uses computational imbalances and communication load, and determines a single cost value.

The resulting metric is unique, as it provides the first model that targets CPC algorithms. It has wide application in Genetic Algorithms, molecular dynamics, scheduling schemes and computational epidemiology. We provide a general method for determining the application-specific constants of the cost metric. As an example, we extract the constants for EpiSimdemics (a highly scalable contagion simulator), and give guidelines for applying the procedure to other CPC algorithms. Our evaluations show that the cost metric estimated the execution times of a contagion simulator with less than a 6.5% error. The metric can be used in optimal assignment of computational resources.

802.11 WLANs do not provide any standardized solution for reliable data multicast. Multicast packets are delivered to multiple clients as a simple broadcast service without support for Automatic Repeat Request. Hence, a fixed low speed (robust) transmission mode is generally used to improve the reliability of multicast files. However, this results in the inefficient use of bandwidth. This paper details a reliable and efficient Wi-Fi multicast delivery solution for use in challenging outdoor environments.

We propose an Application Layer Forward Error Correction enabled data carousel for reliable multicast transmission over standard 802.11 WLANs. To quantify the benefits of the proposed system, results are reported from a cross-layer simulator combining novel outdoor ray-tracing, a Physical layer abstraction simulator (to rapidly quantify the radio performance), a RaptorQ enabled multicast data carousel simulator and an optimal access point deployment tool. The simulation results demonstrate that RaptorQ enabled carousels (compared to standard carousels) significantly reduce the average response time and increase the percentage of satisfied users in a multicast network.

An efficient method for statistically characterizing multiconductor transmission line (MTL) networkssubject to a large number of manufacturing uncertainties is presented. The proposed method achieves its efficiency by leveraging a high-dimensional model representation (HDMR) technique that approximates observables (quantities of interest in MTL networks, such as voltages/currents on mission-critical circuits) in terms of iteratively constructed component functions of only the most significant random variables (parameters that characterize the uncertainties in MTL networks, such as conductor locations and widths, and lumped element values). The efficiency of the proposed scheme is further increased using a multielement probabilistic collocation (ME-PC) method to compute the component functions of the HDMR.

The ME-PC method makes use of generalized polynomial chaos (gPC) expansions to approximate the component functions, where the expansion coefficients are expressed in terms of integrals of the observable over the random domain. These integrals are numerically evaluated and the observable values at the quadrature/collocation points are computed using a fast deterministic simulator. The proposed method is capable of producing accurate statistical information pertinent to an observable that is rapidly varying across a high-dimensional random domain at a computational cost that is significantly lower than that of gPC or Monte Carlo methods. The applicability, efficiency, and accuracy of the method are demonstrated via statistical characterization of frequency-domain voltages in parallel wire, interconnect, and antenna corporate feed networks.

Securing code update is essential for military and health care applications. The functionalists of the sensor nodes in military and health monitoring region depend on their environmental conditions. The sensor nodes will be divided into different multi cast groups based on their location. For each multi cast group a different code update will be sent. We have developed a scheme for secure code update for multi-cast groups.

In order to securely communicate the code update for each multi cast group, a key agreement protocol is developed. This protocol provides confidentiality and immediate authentication. The Protocol is implemented on Tiny OS platform, tested using Tossim simulator and evaluated the Performance. SCUMG protocol is resilient to malicious code update by compromised nodes and provides security against various attacks.

Multiagent systems are widely recognized as a method of choice for realization of distributed time-critical applications for the smart grid. However, no general solutions have been proposed for the difficult task of system development and validation, ready for deployment, which would fully account for the underlying communication network performance. We propose a novel platform designed for this purpose, which integrates a standard multiagent development framework [Java Agent Development (JADE)] and an industry standard communications network simulator (OPNET modeler).

It was realized through generic extensions of the JADE framework to provide discrete event scheduling capabilities, while the OPNET modeler was extended to provide a generic method of associating the network nodes with agents running in JADE. The adopted method adheres to the high-level architecture standard. Importantly, applications developed using this platform may be deployed on the target system without manual modifications. A distributed protection application is presented and the performance is analyzed with respect to candidate agent behaviors and communication scenarios, demonstrating that the feasibility of the application critically depends on the choices made during its design and implementation.

Situational awareness is a critical component in a post-disaster recovery operation for assessment of needs and identification of available resources at different parts of a disaster-affected area. This information, in turn, may help the relief agencies to appropriately coordinate, manage and channelize their resources. A major hindrance in developing such global situational awareness is the non-uniform interaction pattern of relief workers. Volunteers in a particular region have much better knowledge of the local situation than those belonging to regions further away. This information asymmetry leads to deviation in perceptions of volunteers working in different regions, thereby affecting the resource distribution process.

Thus, a unified global situational view of the entire disaster affected area is essential to bridge the perception gap of volunteers and to help them develop a common understanding of the actual scenario. In this paper, we propose a scheme for developing such a coherent global view of the post-disaster situation using local situational information in a smart-phone based delay tolerant peer-to-peer network environment.We focus on generating a comprehensive view which is consistent for all workers irrespective of their location or mobility. The proposed scheme takes into account the spatial locality and spatial regularity properties of human mobility and uses a concept of “opportunistic knowledge injection” to disseminate local situational knowledge to other remote areas without significantnetwork overhead. The effectiveness of the proposal is evaluated on the ONE simulator.

Nowadays, trying to obtain better coverage and performance, and allowed by the low-hardware prices, it is common to deploy a large number of IEEE 802.11 devices in offices, meeting rooms or auditoriums configuring the so called high-density networks. In such a scenario, the shared nature of the transmission medium causes interference problems. Some physical-layer- and link-layer-adaptation mechanisms to palliate those problems have been developed, however, most of them have not been independently implemented and assessed.

In this paper, we implement in a simulator some of the existent solutions, compare them in a simulation environment and show that, in some situations, the existing solutions can lead to a starvation problem. Finally, we propose a new mechanism that manages datarate, transmit power and carrier-sense threshold to ameliorate this problem.