The ubiquity of wireless technologies in the Internet of Things (IoT) concept enforces utilization of power-optimized wireless techniques. Furthermore, a specially tailored mesh-routing algorithm is required in order to achieve battery longevity and node accessibility. In the paper, we propose an improved BLE (Bluetooth Low Energy) mesh-routing algorithm for an IoT Smart Home application. The proposed algorithm is based on a time-slotted medium-access scheme, which enables communication nodes to sleep and/or exchange information. In order to achieve compatibility with any BLE-enabled device, such as mobile phones/tablets, routing and data information is transmitted via Eddystone beacons. Performance analysis of the proposed BLE mesh-routing algorithm is carried out using an OMNeT++ discrete simulation environment and Mixim framework. Validation of the proposed algorithm is completed on the basis of measurements from a real-life test network. The results show that the proposed algorithm is suitable for the IoT applications where the energy efficiency of the communication nodes is a key priority and propagation delays are not critical.

Recent advances in the development of wearable sensors and smartphones open up opportunities for executing computing operations on the devices instead of using them for streaming raw d ...

—Ubiquity of natural disasters during last few decades have risen serious questions towards the prediction of such events and human safety. Every disaster regardless its proportion has a precursor which is manifested as a disruption of some environmental parameter such as temperature, humidity, pressure, vibrations and etc. In order to anticipate and monitor those changes, in this paper we propose an overall system for disaster prediction and monitoring, based on wireless sensor network (WSN). Furthermore, we introduce a modified and simplified WSN routing protocol built on the top of the trickle routing algorithm. Routing algorithm was deployed using the bluetooth low energy protocol in order to achieve low power consumption. Performance of the WSN network was analyzed using a real life system implementation. Estimates of the WSN parameters such as battery life time, network size and packet delay are determined. Based on the performance of the WSN network, proposed system can be utilized for disaster monitoring and prediction due to its low power profile and mesh routing feature.

In this paper we propose an improved adaptive media access (MAC) layer routing algorithm for the broadband power line communication (BPLC) access network founded on the fixed basic approach routing algorithm, which is integrated within the IEEE P1901 standard. The proposed adaptive algorithm incorporates a new dynamically scaled threshold for the selection of the next hop station based on the information from the physical layer. Furthermore, the procedures for the route and the time allocation modifications during the connection setup and later adjustments are developed. Simulation of the new adaptive and existing fixed routing algorithm is performed on the model of a realistic BPLC network using the OMNeT++-based BPLC cross-layer simulator BPlcSim. The simulation results showed that the adaptive routing algorithm outperforms the fixed routing in all aspects, since each station can perform routing functions and make the selection of the most reliable next hop station.

The paper presents a physical (PHY) layer simulation of the low voltage powerline communication (LV PLC) system in accordance with the PRIME standard. The simulation concept is based on the transmission line and two port network theory. The simulator PrimeSim is implemented within the Matlab and introduces a graphical user interface for the network setup and results management. Furthermore, the simulator represents a generic framework for the development of broad spectrum of powerline network simulators and investigation of the applicability of PLC technology for smart grid applications. Performance of the PrimeSim simulator was validated in the pre-built LV PLC network consisting of eight nodes. Results for the probability of the bit error obtained within the simulation represents a good match of those obtained measurement within test network.

This paper describes the specific requirements in the design of versatile wireless sensor networks (WSN) and how MAC routing algorithms influence on their performance. Investigation of the impact of the MAC routing algorithms on the battery consumption of the sensor nodes and packet delivery delay is based on the WSN simulation in OMNET++ framework. Simulation results are validated with the actual measurements using Arduino nodes with XBEE modules.

Abstract—This paper describes the specific requirements inthe design of versatile wireless sensor networks (WSN) andhow MAC routing algorithms influence on their performance.Investigation of the impact of the MAC routing algorithms onthe battery consumption of the sensor nodes is based on theWSN simulation in OMNET++ framework. Simulation resultsare validated with the actual measurements using Arduino nodeswith XBEE modules.Keywords—wireless sensor networks, MAC routing, simulationOzetce —Bu calismada,¸ cok yonlu kablosuz algilayici aglarinin˘tasarimi (WSN) ve MAC yonlendirme algoritmalarinin basarima¸etkisini incelemeyi amaclamaktadir. Algilayici dugumlerinin˘batarya tuketiminde MAC yonlendirme algoritmalarinin etki-lerinin arastirilmasi¸ Algilayici dugumlerin batarya tuketimi MAC˘yonlendirme algoritmalari etkilerinin arastirilmasi¸ WSN benze-timi OMNeT + + ile gerceklenmektedir. Benzetimden elde edilensonuclar XBEE modulleri ile Arduino du˘gumleri kullanarakgercek olcumler ile dogrulanmaktadir.˘Anahtar Kelimeler—dokuman bicimi, stil, anahtar kelimeler.

This paper presents the discrete-event simulator of the low-voltage broadband power line communication (BPLC) access network in accordance with the IEEE P1901 standard. The proposed simulator enables the cross-layer simulation of the physical (PHY) and medium access control (MAC) layer. The performance of the digital communication techniques at the physical layer and the characteristics of the shared medium are integrated at the MAC layer through the probability of the bit error. The proposed simulator was applied in order to estimate the throughput in the simple BPLC network. For the selected set of parameters at the MAC and PHY layer in the test network, the simulator recorded average download throughput of 900kbps, registration time of 36ms and packet delivery ratio of for 0.98 between each station and the HE. DOI: http://dx.doi.org/10.5755/j01.eee.19.5.1440

The paper analyzes the performance of the wireless sensor network (WSN) from the standpoint of routing algorithm related tos battery-discharge process. Using an experimental WSN implemented with Arduino Uno and XBee modules, measurements are made, of the packet delay and battery-discharge rate. Measurement results are compared with the simulation results obtained in the OMNeT++ simulation environment. The paper provides a short overview of difficulties and challenges commonly encountered in WSN design. The measurement results show that Arduino in its native form is not suitable for the WSN processing unit because its high current value during the sleep mode.

This paper presents the comprehensive stochastic model of the TCP (Transmission Control Protocol) that aggregates all TCP states. The model provides the TCP connection throughput for a given packet loss probability, link capacity and link delay. The derived model incorporates assumption that packets coming after the first lost packet are not necessarily lost. Such assumption led to the model which adequately describes TCP behavior. The model derivation required determination of the transitional probabilities between TCP states, number of acknowledged packets and time intervals required for transitions. The obtained stochastic model was confirmed by averaged packet-level simulation results in ns2.

This paper presents one approach to modeling of TCP connection during the slow start phase. Such modeling can be used for TCP connection analysis with reduced computation complexity compared to the packet-level simulators. Proposed model is validated by comparing the results obtained from ns-2 simulations. Introduction Application protocols mainly used on the Internet, such as HTTP or SMTP, use TCP protocol for reliable transport. TCP connection performance analysis can be carried out in two different ways. First one is simulation of TCP connection at the packet-level. This approach leads to accurate results but also requires long simulation time. Alternative approach is to model the TCP behaviour analytically, significantly reducing simulation time while simultaneously keeping accuracy at an acceptable level. This paper reviews models available in the literature and proposes an alternative analytical TCP model during the slow-start phase. TCP behavior can be described with different models. Packet-level models are the most accurate since they employ full TCP stack implementation. However, when analyzing large-scale networks or simple networks with high throughputs, packetlevel simulators are impractical due to long simulation time. An alternative approach is to use mathematical abstractions to model the TCP behavior. One way to abstract the TCP behavior through mathematical tools is to use differential equations. Another approach is based on probability analysis. In this approach, statistical formulas are used to describe TCP behaviour in different stages. Aggregating these models, the full TCP behavior could be obtained. In this paper, a probability model for the slow-start TCP stage is derived. The derived model is validated by comparing the results with the packet-level simulation tool ns-2 [7]. Finally, future directions for employment of probability models of other TCP stages are given. 1 TCP Protocol TCP is a reliable connection-oriented transport protocol for packet-switched networks. Reliability is achieved by employing acknowledgements (ACKs) [2]. Using ACKs and sequence numbers, the transmitter keeps the track of packets that are successfully delivered to the receiver. TCP operates in different stages: Slow Start, Congestion Avoidance, Fast Retransmit, Fast Recovery and Timeout. Transition between stages is determined by packet loss or acknowledgement of predefined number of packets. The window size determines the maximum number of packets that a transmitter may send before receiving the first acknowledgement. In the Slow Start phase, window size is incremented with every received ACK. Time interval, from departure of the first packet to the last packet in a window, represents round. The window size varies with the rate of the packet loss in the network. Hence, the packet loss probability increases with the number of sent packets due to the congestion in the network. Generally, window size wi grows in rounds and can be expressed as: 1 0 1 1 1 1 1 1 1 − − − − − ⋅ = ⋅ = + ⋅ = + = i i i i i i w w b w w b w w γ γ (1) where b is number of packets acknowledge by one ACK, and i is the round number and w0 is the initial window size. Total number of packets sent in slow start including the round i is 1 1 0 0 1 2 0 0 − − ⋅ = ⋅ + + + ⋅ + = − γ γ γ γ γ i i i w w w w ssdata (2) When a packet loss occurs during the slow start stage, there are two mechanisms to detect it. The first mechanism detects packet loss by using timeouts (TO). The second mechanism detects packet loss upon receiving three duplicate ACKs. SNE Simulation Notes Europe – Print ISSN 2305-9974 | Online ISSN 2306-0271 SNE 21(1), 2011, 45-48 | doi: 10.11128/sne.21.sn.10047 A Gogic et al. Probability Model for TCP Slow Start 46 SNE 21(1) – 4/2011 TN 2 Approaches for Modelling the Packet Switched Networks There are several approaches for modeling packet switched networks. The most accurate network models are packet-level models that keep track of individual packets. These models are implemented in network simulators, such as ns-2 [7]. The main drawback of packet-level model is a large computational effort required to keep track of each virtual packet in large scale simulations. Analytical models are based on idea to model the TCP network mathematically in order to reduce complexity involved in simulations [1, 6]. These models do not consider the network dynamics. They assume that round-trip time and loss probability are constant and there are no interactions between TCP flows. Fluid models are intended for simulation of packet networks. They overcome network scalability problem by keeping track of average quantities for relevant network parameters [5, 4]. Additionally, they use assumption that the bit rates are piecewise constant. Hybrid models use continuous time state variables with discrete time events [3]. Hybrid simulations require significantly less computational resources than packet level simulators. However, solution of hybrid equations is still necessary in order to simulate networks. 3 Probability Model for TCP Slowstart Stage There are two approaches for creating probability models of TCP behaviour. The source centric model assumes that packets leave the source with a certain loss probability [1]. The assumption taken by the second model is that the network generates loss probabilities for each packet [5]. Thus, the arrival process is represented by Poisson random process. In this paper we use the first approach with the further assumptions: the packet losses in two successive rounds are not correlated, packet loss occurs only in the forward direction; packet losses are independent of window size. Model detects packet losses by triple duplicates and TOs. Based on the source-centric model [1,6], we derived the expected value of number of packets sent in the slow start phase as a function of packet loss probability p, the initial size of congestion window wi and the number of packets acknowledged by one ACK. We further distinguish two boundary cases related to the position where packet was lost. The first case is characterized by the packet loss occurring at the beginning of the round (Figure 1). For the second case, the packet loss occurs at the end of the round (Figure 2). Figure 1. Slow-start phase, packet drop occurred at beginning of the round i. Figure 1 shows the number of acknowledge packets -1. Taking into consideration equation (2), we can write

The paper presents a simple implementation model of the high-voltage power line communication (HV PLC) channel using digital filters. The model utilizes three identical finite impulse response (FIR) filters. The amplitude characteristic of the FIR filters matches the HV PLC channel amplitude characteristic for a given coupling, without taking into consideration reflection. The reflection phenomenon occurring at the HV power line terminals is implemented in the model by using a parallel feedback branch and additional filter delay corresponding to the traveling time of the reflected wave. The approach presented in this paper is applied to a 400 kV power line with three phase conductors in horizontal disposition. Results are given for two optimal couplings, middle phase to ground and outer phase to middle phase coupling.