Routing Management Research Articles

A Novel Compressed Sensing Technique for Traffic Matrix Estimation of Software Defined Cloud Networks

Traffic Matrix estimation has always caught attention from researchers for better network management and future planning. With the advent of high traffic loads due to Cloud Computing platforms and Software Defined Networking based tunable routing and traffic management algorithms on the Internet, it is more necessary as ever to be able to predict current and future traffic volumes on the network. For large networks such origin-destination traffic prediction problem takes the form of a large under-constrained and under-determined system of equations with a dynamic measurement matrix. In this work, we present our Compressed Sensing with Dynamic Model Estimation (CS-DME) architecture suitable for modern software defined networks. Our main contributions are: (1) we formulate an approach in which measurement matrix in the compressed sensing scheme can be accurately and dynamically estimated through a reformulation of the problem based on traffic demands. (2) We show that the problem formulation using a dynamic measurement matrix based on instantaneous traffic demands may be used instead of a stationary binary routing matrix which is more suitable to modern Software Defined Networks that are constantly evolving in terms of routing by inspection of its Eigen Spectrum using two real world datasets. (3) We also show that linking this compressed measurement matrix dynamically with the measured parameters can lead to acceptable estimation of Origin Destination (OD) Traffic flows with marginally poor results with other state-of-art schemes relying on fixed measurement matrices. (4) Furthermore, using this compressed reformulated problem, a new strategy for selection of vantage points for most efficient traffic matrix estimation is also presented through a secondary compression technique based on subset of link measurements.

Sources of fish in the ephemeral western iishana region of the Cuvelai–Etosha Basin in Angola and Namibia

The triangle between the Kavango and Kunene rivers is drained by the Cuvelai, an ephemeral and deltaic drainage system covering more than 100 000 km2. In good rainfall years, the area becomes populated by fish communities dominated by five species migrating southward towards the endorheic Etosha Pan, the basin’s terminal sump. When water dries up, fish subsequently die-off and their sudden appearance in rainy years has captivated scientists for decades. The current study was prompted by hitherto untapped indigenous knowledge through narratives of opportunistic fish harvesting of migrating fish at temporary connections between the Kunene River and the Cuvelai- Etosha Basin. A reconnaissance fish survey in 2017 was complemented by digital satellite images and elevation data analyses. Results support the presence of at least three major ephemeral fish migration routes. The dominant fish genera migrating upstream in Kunene tributaries comprise Enteromius, Oreochromis and Clarias, all eurytopic and known to undertake upstream, lateral and downstream migrations on floodplains. Although other notable fish refugia in the Cuvelai–Etosha Basin are yet to be identified, there is a necessity for the protection and management of these migration routes in tandem with studies on the nature and extent of this inter-basin fish migration under climate change and variability.

Визуальное обеспечение творческой разработки программных систем

Визуальное обеспечение творческой разработки программных систем

Solving N-Queens Problem Using Subproblems based on Genetic Algorithm

<span lang="EN-US">Nowadays, permutation problems with large state spaces and the path to solution is irrelevant such as N-Queens problem has the same general property for many important applications such as integrated-circuit design, factory-floor layout, job-shop scheduling, automatic programming, telecommunications network optimization, vehicle routing, and portfolio management. Therefore, methods which are able to find a solution are very important. Genetic algorithm (GA) is one the most well-known methods for solving N-Queens problem and applicable to a wide range of permutation problems. In the absence of specialized solution for a particular problem, genetic algorithm would be efficient. But holism and random choices cause problem for genetic algorithm in searching large state spaces. So, the efficiency of this algorithm would be demoted when the size of state space of the problem grows exponentially. In this paper, the subproblems used based on genetic algorithm to cover this weakness. This proposed method is trying to provide partial view for genetic algorithm by locally searching the state space. This method works to take shorter steps toward the solution. To find the first solution and other solutions in N-Queens problem using proposed method: dividing N-Queens problem into subproblems, which configuring initial population of genetic algorithm. The proposed method is evaluated and compares it with two similar methods that indicate the amount of performance improvement.</span>

Realization of VANET-Based Cloud Services through Named Data Networking

Connected car technology (also referred to as VANET) has gradually paved its way to legislation in several countries and soon will be followed by mass-scale deployment. However, the race between the advancements in technologies and utilization of the available resources have left a question mark on the future of pure VANET. Therefore, the research community together with academia and industry have foreseen the evolution of VANET into VANET-based clouds. The data- or content-centric communication paradigm is the point of convergence in these technologies because the content is shared among different nodes in different forms such as infotainment or safety. However, the current IP-based networking is not an ideal choice for content-centric applications because of its larger overhead for establishing, maintaining, and securing the path, addressing complexity, non-scalability for content, routing and mobility management overhead, and so on. Therefore, the limitations and shortcomings of current IP-based networking and the need for efficient content delivery advocate for a paradigm shift. To this end, a new content-centric networking paradigm, namely NDN, has been employed to address the aforementioned issues related to content-centric networking while using IP-based networking. In this article, we foresee the integration of VANET-based clouds with NDN called NDN-VC for reliable, efficient, robust, and safe intelligent transportation systems. We particularly aim at the architecture and concise naming mechanism for NDN-VC. Furthermore, we also outline the unique future challenges faced by the NDN-VC.

МЕТОДИКА ОЦІНКИ ЕФЕКТИВНОСТІ СИСТЕМИ УПРАВЛІННЯ ТЕЛЕКОМУНІКАЦІЙНИМИ МЕРЕЖАМИ

The article analyzes existing approaches and methods for assessing the efficiency of a telecommunication network and its management system. The concept of efficiency, classification and existing approaches to its evaluation are considered. A number of indicators of telecommunication network efficiency characterizing the target, technical (technological), economic efficiency of the telecommunication network are given. The indicators of efficiency of the telecommunication network management system are considered. The method of estimation of efficiency of routing methods as a subsystem of routing management of a telecommunication network management system, which consists of seven stages, is presented. Indicators of the effectiveness of routing methods are considered as three groups of indicators, which are divided into global, local and operational financial. The efficiency of routing methods (by parameters of productivity, packet delay time) is given when changing the topology and different routing methods for fixed input load and network dimension. It is shown that the efficiency of the control system is determined by the efficiency of the telecommunication network.

Evacuation paths in historic city centres: A holistic methodology for assessing their seismic risk

During seismic emergencies in historical urban scenarios, evacuation paths can suffer significant damages and modifications due to both extrinsic (i.e.: building facing the path) and intrinsic (i.e.: pavements state, the presence of underground lifelines or hypogeum) vulnerabilities. Such damages and modifications can hinder the population's evacuation and the first responders’ intervention, mainly because of paths' blockage or unavailability in emergency conditions. Paths’ safety is additionally affected by populations’ exposure conditions, also due to individuals’ motion in the post-earthquake environment. Hence, an analysis of factors influencing the seismic risk of evacuation paths and a consequent evaluation of their safety during the emergency are thus desirable. This work aims to offer a preliminary and quick holistic method for seismic risk assessment and damage level estimation of possible evacuation paths. Firstly, data about safety influencing factors (i.e.: path use and exposure; geometric features; physical-structural features; extrinsic vulnerability; seismic hazard) are collected, associated to related weights and organized in risk indexes according to three calculation approaches. Then, according to real-world data, a correlation about path risk-damage levels is proposed with the additional purpose to evaluate the method capabilities in describing post-earthquake scenarios. Obtained results evidence that the proposed methodology could help safety designers in the seismic emergency planning of urban paths (i.e.: by means of risk maps) by including the management of population's evacuation routes towards assembly points, the optimization of rescuers’ activities and the promotion of different priorities of interventions on building heritage.

Визуальное обеспечение творческой разработки программных систем

Визуальное обеспечение творческой разработки программных систем

A Single Airport Time Slot Allocation Method Considering Scheduling Delay and Operational Delay

At present, when flight seasonal routing management departments make the flight plans, there is a lack of quantitative assessment of the actual execution of the delay together with the technology for finding the potential key link of flight delays. In order to enhance the scientificity and rationality of flight seasonal scheduling, this paper proposes a flight schedule optimization model based on historical data, for the purpose of reducing airline’s request deviation, i.e., the time difference between allocated time slots and airline requets and operational delays. This model construct an object function which make the total operating and planned delay minimum and firstly introduce corridor capacity as constraint. In the experimental part based on the historical data of Hangzhou Xiaoshan Airport, we use Hungarian algorithm to give solutions of this model and prove the feasibility and effectiveness.

Mobile Matrix: Routing under mobility in IoT, IoMT, and Social IoT

The explosive growth of “things” connected to the Internet (Internet of Things, IoT) raises the question of whether existing ready-to-go networking protocols are enough to cover social and mobile IoT’s demands. IoT aims to interconnect static devices attached to some physical infrastructure. However, mobility is a major factor present in everyday life, and naturally the “things” can move around (Internet of Mobile Things, IoMT) and create social ties (Social IoT, SIoT) in the cyber-physical space. In that context, we present Mobile Matrix (μMatrix), a routing protocol that uses hierarchical IPv6 address allocation to perform any-to-any routing and mobility management without changing a node’s address. In this way, device mobility is transparent to the application level favoring IoMT and SIoT implementation and broader adoption. The protocol has low memory footprint, adjustable control message overhead, and it achieves optimal routing path distortion. Moreover, it does not rely on any particular hardware for mobility detection (a key open issue), such as an accelerometer. Instead, it uses a passive mechanism to detect that a device has moved. We present analytic proofs for the computational complexity and efficiency of μMatrix, as well as an evaluation of the protocol through simulations. We evaluate the protocol performance under human and non-human mobility models. For human mobility, we generated mobility traces using Group Regularity Mobility (GRM) Model, setting its parameters based on real human mobility traces. For the non-human mobility, we propose a new mobility model, to which we refer as Cyclical Random Waypoint (CRWP), where nodes move using a simple Random Waypoint and, eventually, return to their initial position. We compared μMatrix with three baseline protocols: Routing Protocol for low-power and lossy networks (RPL), Mobility Management RPL (MMRPL), and Ad hoc On-Demand Distance Vector (AODV). The results show that μMatrix and RPL offer ≈ 99.9% of bottom-up delivery rate, but only μMatrix offer ≥ 95% of top-down traffic in highly dynamic and mobile scenarios, while other protocols ≤ 75%. Moreover, μMatrix uses up to 65% of the routing table while RPL and AODV fulfill theirs in all scenarios, which leads to poor top-down and any-to-any reliability.

일제시기 조선우선주식회사의 阪神航路 경영 : 선항(동맹)회의 결성과 조선미 수송을 중심으로

일제시기 조선우선주식회사의 阪神航路 경영 : 선항(동맹)회의 결성과 조선미 수송을 중심으로

A FRAMEWORK FOR COMPARATIVE ANALYSIS OF WSN ATTACKS AND COUNTER MEASURES RECOMMENDATIONS

Abstract— The growth in the need for customized services in hand held devices and sensor based applications are continuously motivating the wireless networks, wireless communications and wireless infrastructures. In the last decade the wireless communication has evolved around the MANETs and IoT devices. Nevertheless, the demands for wireless sensors have not decreased due to less costly and simple deployments measures. The wireless networks especially running on the tiny operating systems are designed and programmed to perform very specific tasks. Also, the processing capabilities of these devices are limited. Henceforth, it is difficult to incorporate additional services into the devices such as routing management, data processing or security. The routing management protocols or the data processing frameworks are often the essential part of the framework. Nevertheless, due to the bottleneck between performance and service availability, the service providers ignore the security issues. Considering the wide use of the wireless sensors ranging from healthcare to tactical usage, it is the demand of the modern research to re-address the security measures of the wireless sensor network. In the recent past, the researchers and practitioners have witnessed a number of attacks on WSN infrastructures and policies. The attacks were diversified in terms of distortions of the information, damage to the network or sometimes vulnerability to the user identifications. Hence, none of the single frameworks are capable of detect all types of attacks on WSN. It is been observed that during any attacks on the WSN, the parametric values related to power, energy and response time changes drastically. Henceforth, any measure of the changes and continuous monitoring may lead to finding a pattern in the data tenting to standard formulations. Thus this work proposes a novel framework to detect the behavioural malfunction of the wireless sensor networks based on the energy, power consumption and response time of the nodes. This is proposed to be the major outcome of this work. Yet another novel outcome of this work is to associate the detection model with the attack response knowledge base in order to generate timely recommendations to avoid the damages. The objective of this work is to create a responsive system for controlling the damages caused by any attack on wireless sensor network for making the world of wireless communication more trustable.

RABP: Delay/disruption tolerant network routing and buffer management algorithm based on weight

Delay/disruption tolerant network is a novel network architecture, which is mainly used to provide interoperability for many challenging networks such as wireless sensor network, ad hoc networks, and satellite networks. Delay/disruption tolerant network has extremely limited network resources, and there is typically no complete path between the source and destination. To increase the message delivery reliability, several multiple copy routing algorithms have been used. However, only a few can be applied efficiently when there is a resource constraint. In this article, a delay/disruption tolerant network routing and buffer management algorithm based on weight (RABP) is proposed. This algorithm estimates the message delay and hop count to the destination node in order to construct a weight function of the delay and hop count. A node with the least weight value will be selected as the relay node, and the algorithm implements buffer management based on the weight of the message carried by the node, for efficiently utilizing the limited network resources. Simulation results show that the RABP algorithm outperforms the Epidemic, Prophet, and Spray and wait routing algorithms in terms of the message delivery ratio, average delay, network overhead, and average hop count.

OpenSIP: Toward Software-Defined SIP Networking

VoIP is becoming a low-priced and efficient replacement for PSTN in communication industries. With a widely growing adoption rate, SIP is an application layer signaling protocol, standardized by the IETF, for creating, modifying, and terminating VoIP sessions. Generally speaking, SIP routes a call request to its destination by using SIP proxies. With the increasing use of SIP, traditional configurations pose certain drawbacks, such as ineffective routing, un-optimized management of proxy resources (including CPU and memory), and overload conditions. This paper presents OpenSIP to upgrade the SIP network framework with emerging technologies, such as SDN and NFV. SDN provides for management that decouples the data and control planes along with a software-based centralized control that results in effective routing and resource management. Moreover, NFV assists SDN by virtualizing various network devices and functions. However, current SDN elements limit the inspected fields to layer 2-4 headers, whereas SIP routing information resides in the layer-7 header. A benefit of OpenSIP is that it enforces policies on SIP networking that are agnostic to higher layers with the aid of a Deep Packet Inspection (DPI) engine. Among the benefits of OpenSIP is programmability, cost reduction, unified management, routing, as well as efficient load balancing. The present study implements OpenSIP on a real testbed which includes Open vSwitch and the Floodlight controller. The results show that the proposed architecture has a low overhead and satisfactory performance and, in addition, can take advantage of a flexible scale-out design during application deployment.

An SDN‐based scalable routing and resource management model for service provider networks

SummaryVolume of the Internet traffic has increased significantly in recent years. Service providers (SPs) are now striving to make resource management and considering dynamically changing large volume of network traffic. In this context, software defined networking (SDN) has been alluring the attention of SPs, as it provides virtualization, programmability, ease of management, and so on. Yet severe scalability issues are one of the key challenges of the SDN due to its centralized architecture. First of all, SDN controller may become the bottleneck as the number of flows and switches increase. It is because routing and admission control decisions are made per flow basis by the controller. Second, there is a signaling overhead between the controller and switches since the controller makes decisions on behalf of them. In line with the aforementioned explanations, this paper proposes an SDN‐based scalable routing and resource management model (SRRM) for SPs. The proposed model is twofold. SRRM performs routing, admission control, and signaling operations (RASOs) in a scalable manner. Additionally, resource management has also been accomplished to increase link use. To achieve high degree of scalability and resource use, pre‐established paths (PEPs) between each edge node in the domain are provided. The proposed controller performs RASOs based on PEPs. The controller also balances the load of PEPs and adjusts their path capacities dynamically to increase resource use. Experimental results show that SRRM can successfully perform RASOs in a scalable way and also increase link use even under heavy traffic loads.

Fuzzy Logic Based Distance and Energy-Aware Routing Protocol in Delay-Tolerant Mobile Sensor Networks

In challenged networks such as Wireless Sensor Networks, limitations such as nodes mobility, short radio range and sparse network density can prevent communications among nodes. Consequently, it can result in long delays in exchanging messages among nodes. Designing Delay-Tolerant Networks is considered to be an approach for dealing with lengthy breakdown of communication between nodes. Using multi-replica methods seems rational for these networks. However, a majority of these methods inject a large amount of replications of a message in the network so as to enhance message delivery probability which consequently leads to the loss of energy and reduction of network efficiency. Two major issues should be considered to achieve data delivery in such challenging networking environments: a routing strategy for the network and a buffer management policy. This study proposes a new routing protocol called Fuzzy-Logic based Distance and Energy Aware Routing protocol (FLDEAR) in delay tolerant mobile sensor network. A FLDEAR is a distance and energy aware protocol that reduces the number of message replications and uses two fuzzy inference systems in routing and buffer management. The results of conducted simulations indicated that this routing algorithm can be used for enhancing data packet delivery ratios and reducing data transmission overhead than several current Delay-Tolerant Mobile Sensor Networks routing protocols.

Optimal production, replenishment, delivery, routing and inventory management policies for products with perishable inventory

This paper presents a generalized production-inventory-routing model with perishable inventory. We analyze the optimal integrated decisions of when and how much to deliver and sell products with varying manufacturing periods. We discuss main inventory management policies to demonstrate the applicability of the model in real-world applications for production routing problems (PRPs) with perishable inventory. Furthermore, an exact branch-and-cut algorithm is developed and discussed. We introduce new families of logical, strengthened lot-sizing and lifted Miller–Tucker–Zemlin subtour elimination constraints for the PRP with perishable inventory. Finally, we test the performance of the algorithm. We also implement and compare 8 suboptimal delivery and selling priority policies with an optimized policy to develop managerial implications.

Data for: Optimal production, replenishment, delivery, routing and inventory management policies for products with perishable inventory

Abstract This paper presents a generalized production-inventory-routing model with perishable inventory. We analyze the optimal integrated decisions of when and how much to deliver and sell products with varying manufacturing periods. We discuss main inventory management policies to demonstrate the applicability of the model in real-world applications for production routing problems (PRPs) with perishable inventory. Furthermore, an exact branch-and-cut algorithm is developed and discussed. We introduce new families of logical, strengthened lot-sizing and lifted Miller–Tucker–Zemlin subtour elimination constraints for the PRP with perishable inventory. Finally, we test the performance of the algorithm. We also implement and compare 8 suboptimal delivery and selling priority policies with an optimized policy to develop managerial implications.

Sistema de ayuda a la decisión espacial para la distribución de concentrado en alimentación anima

The management of the distribution of concentrates is a process that requires a great organizational effort, given the large number of elements of the supply chain involved. In this work a case study is related, in which a spatial decision aid tool for the management of concentrate distribution logistics has been developed and implemented. The objective when talking about effective distribution management should not be relegated only to a search in the reduction of km traveled by vehicles, but should be considered from a more ambitious perspective, pursuing a better organization of production and a leveling of the activity. Consequently, the logistics of distribution will not only involve transport vehicles, but will require the involvement of the production, ordering and transport areas, as evidenced in this work. Route management must be integrated with an adequate consumption forecasting capacity, which allows orders to be served before the date on which the safety stock is reached, considering also the production capacity of the manufacturing plant. To evaluate the viability of the tool designed, the results relative to km traveled and tons distributed prior to its implementation were compared with those obtained afterwards. The results obtained reflect a significant saving derived from the use of the developed tools, although these savings have come more from a better management of the orders than from an improvement in the management of vehicle routes. Consequently, additional efforts will be necessary in the route management management tool in order to reduce the participation of the manager in the re-elaboration of the routes proposed by the spatial decision support system.

Analysis of patient flows in elective surgery: modelling and optimisation of the hospitalisation process

Rationalising costs while guaranteeing a good quality of service is a challenge that healthcare systems are currently facing. In elective surgery departments, as operations can be scheduled in advance, the goal is usually to maximise the utilisation index of the operating theatre. Nevertheless, the optimisation of a single stage of the process is pointless without an efficient management of the entire routing from income to dismissal. The paper presents discrete events simulation of the actual patient flows in elective surgery exploiting the recovery logs of a hospital department. A UML activity diagram of the surgery process together with the collected hospital data have been used to build a stochastic model of queuing network, identify its parameters and conduct different simulated experiments in order to select the solution that best optimises the performances of the system. The simulation results have shown that there is a large variation in waiting times in correspondence to small variations of the average value of the inter-arrival times. Therefore, solutions that optimise utilisation indexes of both beds and operating theatres should consider a concurrent effort to reduce the variance of admittance processes, otherwise the waiting times will lengthen beyond acceptable limits.