Long-Range Wide-Area Network (LoRaWAN) is receiving wide acceptance by offering long-distance, low-power, robust, and cost-effective communication of sensory data to the server. LoRaWAN end devices open two receive windows to receive a downlink after the transmission of data to the server. However, optimizing the delay in opening these receive windows (known as RXDelay) is pivotal for efficient uplink and downlink communication. This task becomes even more challenging when application requirements change over time. To address such challenges, this paper proposes a novel approach to estimate and configure the optimal RXDelay of end devices. By leveraging the concept of the age of information at the network server, the proposed approach dynamically adapts RXDelay based on the specific demands of different scenarios, allowing for timely data transmission. Through extensive experimentation and evaluation on a real-world LoRaWAN deployment, the proposed approach demonstrates significant improvements in communication efficiency and overall network performance. Specifically, it outperforms existing methods in packet reception rate and energy efficiency for both confirmed and unconfirmed messages across diverse network conditions, while still ensuring a balanced throughput.

In a virtualized software defined network (VSDN), PACKET_IN messages of switches must pass through the hypervisor in order to reach the corresponding controller. Hence, the latency experienced by a network element is the sum of latency from network element to hypervisor and the latency from the hypervisor to the controller corresponding to the network element. Therefore, the locations of both the hypervisors and controllers determine the latency of network elements in a virtualized environment. In this paper, we propose a strategy for determining the placement of controllers in a VSDN while fixing the hypervisor(s) in the physical network. We also propose an approach for jointly optimizing the placement of hypervisors and controllers in a VSDN. The objective is to minimize the worst case latency between the network element and its corresponding controller. Furthermore, we propose a generalized model which can be used not only to optimize the worst case latency, but also to optimize other objectives such as the average latency, the maximum average latency, and the average maximum latency. The proposed problems are formulated as integer linear programs. We evaluated the performance of our proposed strategies using the AT&T network of Internet Topology Zoo and the Internet 2 OS3E topology, and compared with the hypervisor placement problem. Evaluations demonstrate that the proposed methods outperform the existing hypervisor placement approach with respect to the various performance metrics.

Recent advances in robotics and low-power embedded systems made three-dimensional (3D) mobile wireless sensor networks (MSNs) an effective solution for monitoring a field of interest (FoI). From a cost perspective, it is often important to ensure the desired coverage ratio for the FoI within a maximum allowable response (MAR) time, by using a minimum number of sensors in MSNs. The literature on determining the minimum number of sensors for the desired coverage ratio assumes that the FoI is unbounded to overcome the border effects. Since the entire sensing sphere of the sensors near the boundary may not be useful for the coverage, the number of sensors estimated without the border effects is lower than the actual value. In this paper, we estimate the minimum number of sensors required to achieve a desired coverage ratio in a given MAR time for a 3D FoI. We term this problem (α; V; T)-coverage problem, where a, V , and T are the desired coverage ratio, average speed of sensors, and MAR time, respectively. We assume straight line mobility model for the sensors and consider the border effects while deriving the expected sensing volume of a sensor useful in coverage. We also consider the restriction of sampling rate of the sensors in this analysis. We discuss the application of our analysis for a non-hyper-rectangle shaped FoI, random walk, and waypoint mobility models, and also the impact of neglecting the border effects. Our numerical and simulation results demonstrate the significance of border effects on the number of sensors and also the relationship between the coverage ratio, MAR time, sampling period, and the sensing range.

Software defined networking shifts the control plane of forwarding devices to one or more external entities known as controllers. Determining the optimal location of controllers in the network and the assignment of switches to them is widely known as controller placement problem. In case of controller failures, the switches are disconnected from the controller until they are reassigned to other active controllers with enough spare capacity. However, there is a significant upsurge in the worst case latency after the reassignment due to lack of planning for controller failures. In this paper, we propose a controller placement strategy that not only considers reliability and capacity of controllers but also plans ahead for controller failures to avoid repeated administrative intervention, drastic increase in latency and disconnections. It is formulated as a mixed integer linear program. The objective is to minimize the maximum, for all switches, of the sum of the latency from the switch to the nearest controller with enough capacity (first reference controller) and the latency from the first reference controller to its closest controller with enough capacity (second reference controller). We also proposed a generalized model which can be used to minimize the average latency and extended it for multiple controller failures. Furthermore, we presented a simulated annealing heuristic that efficiently solves the problem on large scale networks. The proposed formulation and heuristic are evaluated on various networks from the Internet Topology Zoo. Simulation results show that our proposed method performs better than the controller placement that does not plan ahead for failures.

Coverage and connectivity are important metrics used to evaluate the quality of service of wireless sensor networks (WSNs) monitoring a field of interest (FoI). Most of the literature assumes that the sensors are deployed directly in the FoI. In this paper we assume that the sensors are stochastically deployed outside the FoI. For such WSNs, we derive probabilistic expressions for k-coverage and connectivity using exact geometry. We validate our analysis and demonstrate its utility to estimate the minimum number of sensors required for a desired level of coverage and connectivity. We also demonstrate an on-campus traffic monitoring system to count the number of vehicles, detect the direction of vehicle, and to identify the vehicle (two-wheeler or four-wheeler) using sensors along both sides of the road.

Data centers are over provisioned to handle traffic surges. However, various studies of data center traffic regarded this upsurge as a rare event and shown that the resources of data center are underutilized. Hence, there is a need to conserve energy by providing control knobs that turn the resources of data center on/off according to the traffic condition. In this paper, we study the ability of 4-4, 1-4 data center network design for energy conservation. Given a set of current flows, we propose a greedy approach to find sub-network that can accommodate current set of flows and switch off rest of the network to conserve energy. We simulated the proposed method using network-simulator (NS3) and compared the performance with Elastic Tree. The simulation results shown performance of 4-4, 1-4 design is better than Elastic Tree in terms of energy conservation, packet delivery ratio and delay. As an extension, we also compared the support from routing protocols: source routing and location based routing, in designing energy conservation methods.

Coverage is an important metric used to measure the quality of service of wireless sensor networks monitoring a field of interest (FoI). Existing literature on the coverage problem assumes that the sensors are deployed directly in the FoI. These results cannot be applied in some applications like canal water surface monitoring, because the sensors cannot be deployed on the water surface. In this paper, we analyze the coverage problem in applications where, the sensors are deployed uniformly at random outside the FoI near the boundary. We derive the expected value of the effective sensing area useful for k-coverage of the FoI using exact geometry. We demonstrate the utility of the analysis in estimation of the minimum number of sensors required for a desired level of coverage. With numerical results we show the impact of various parameters on the number of sensors.

Coverage is an important metric to measure the quality of service of a wireless sensor network monitoring a field of interest (FoI). From an energy perspective, it is often very important to maintain the desired coverage ratio with a minimum number of sensors. The literature on determining the critical sensor density (CSD) for the desired coverage ratio assumes that the FoI is unbounded or toroidal in shape. Although it is not a realistic assumption, it eliminates the border effects in analysis. Since the entire sensing area of the sensors near the boundary may not be useful for the coverage, the CSD estimated without the border effects is lower than the actual value. In this paper, we assume that the sensors are deployed uniformly at random in a convex polygon-shaped FoI and consider the border effects to derive the expected sensing area of a sensor used in the coverage. Next, we estimate the CSD required for the desired coverage ratio. We validate the analysis and demonstrate the impact of border effects on CSD using numerical results. Results show that our approach estimates the CSD better than another one that does not consider the exact geometry of the FoI.

A heterogeneous wireless sensor network (WSN) consists of sensors with unequal ranges of sensing and/or communication. In a dense WSN, a part of the region covered by a sensor may also be covered redundantly by a neighbouring sensor. In this paper, we analyse the redundancy in the coverage of a heterogeneous WSN and define the redundancy degree of a sensor. We follow a probabilistic approach to derive the expected redundancy degree of a sensor with a given number of sensors of each type in the neighbourhood. We demonstrate the accuracy of the analysis, and study the impact of the number of sensors of different types on the expected redundancy degree with numerical and simulation results. We also demonstrate an application of the redundancy analysis in the design of a heterogeneous WSN. We propose an algorithm to determine the minimum number of sensors of different types required to satisfy the desired coverage ratio and simultaneously minimise the cost of the network.

The increasing complexity and sophistication of the applications deployed on Data Center Network (DCN) demanded new features and greater performance from the DCN. This resulted in many designs addressing various challenges such as cost, performance, reliability, scalability, security and energy. One major challenge a designer often faces is the realization of their proposed design or realization of the existing designs for comparison. Although proto-typing is a better choice but it does have certain limitation and is very complex and expensive. Hence, Simulation is considered as an alternative to the prototyping. In this paper, we present a case study of using Network Simulator 3 (NS3) for realization of various architectures for DCN and study their performance. The information we provide includes realization of the most popular designs for DCN and tools available with NS3 to study their performance. Our effort is to make it easy for a beginner to build popular designs for DCN and study their performance using NS3.

Architecture plays an important role in the design of Data Center Networks (DCN). Designs for DCN are to be scalable, robust and efficient. There are many designs proposed in recent years where routing is performed using location information of the server. These designs solve scalability problem of IP and Ethernet with additional overhead of determining and maintaining location information of the server. In this paper, we propose a new architecture named, four-four, one-four architecture (4-4, 1-4 Architecture) that has evolved from the format of IP address. Addressing and interconnection used in our design eliminate the complexities in the previous designs such as constructing addresses based on location information. Two major benefits - reduction of entries in routing table and routing based on location information - are achieved through our design with minimum complexity. The first advantage is due to the design combining servers with common prefixes at each level using hierarchical format of IP address. The second advantage is due to the IP address assigned to servers and switches acting as location indicator. This helps in faster routing where packet forwarding is done based on the bits of IP addresses. Further, the proposed architecture meets major design requirements for data center networks such as load balancing and energy conservation.