About Omnet Project Team

With the potential to generate numerous connection requests, an explosive growth in the volume of data traffic and the number of mobile and machine-to-machine (M2M) devices has drawn new attention on the radio access network (RAN). Surging random access attempts cause not only severe preamble collisions but also down-link resource shortage, and thus degrade the performance of random access procedure. However, the effect of down-link resource shortage on system performance is not yet comprehensively studied.

In addition, most existing random access contention resolution mechanisms sacrifice RACH (random access channel) throughput for a high success probability, and thus the price is that low-throughput mechanisms need long time to deal with access attempts. In this work, we evaluate the MAC-level performance for the 4-step random access procedure in LTE systems, for both with and without constrained down-link resources. Further, we propose a novel RACH contention resolution scheme, the dynamic backoff (DB) scheme. DB can achieve high RACH throughput yielding a high random access success probability under various RACH overloaded scenarios.

IEEE 802.11ah task group is working on a new amendment of the IEEE 802.11 standard, suitable for high density WLAN networks in the sub 1 GHz band. It is expected to be the prevalent standard in many Internet of Things (IoT) and Machine to Machine (M2M) applications where it will support long-range and energy-efficient communication in dense network environments. Therefore, significant changes in the legacy 802.11 standards have been proposed to improve the network performance in high contention scenarios, most important of which is the Restricted Access Window (RAW) mechanism described in the amendment.

In this paper we analyze the performance of the RAW mechanism in the Non-Cross Slot Boundary case under various possible holding schemes. We propose new holding schemes as well as a new grouping scheme for RAW mechanism based on back-off states of the stations. The proposed schemes are shown to improve the saturation throughput and energy efficiency of the network through extensive simulations. These schemes can therefore be adapted in practical deployment scenarios of the IEEE 802.11ah use cases to improve the overall network performance. Overall, these advanced features make 802.11ah standard a true IoT-enabling technology towards seamless integration of massive amount of connected devices in the future.

Device-to-device (D2D) communication commonly refers to a type of technology that enable devices to communicate directly with each other without communication infrastructures such as access points (APs) or base stations (BSs). Bluetooth and WiFi-Direct are the two most popular D2D techniques, both working in the unlicensed industrial, scientific and medical (ISM) bands. Cellular networks, on the other hand, do not support direct over-the-air communications between users and devices.

However, with the emergence of context-aware applications and the accelerating growth of Machine-to-Machine (M2M) applications, D2D communication plays an increasingly important role. It facilitates the discovery of geographically close devices, and enables direct communications between these proximate devices, which improves communication capability and reduces communication delay and power consumption. To embrace the emerging market  that that requires D2D communications, mobile operators and vendors are accepting D2D as a part of the fourth generation (4G) Long Term Evolution (LTE)-Advanced standard in 3rd Generation Partnership Project (3GPP) Release 12.

We are witnessing an ever-increasing demand for cloud computing services, IoT, M2Mcommunications and advanced telecom applications. In addition, other applications like commerce, medical care, education, entertainment, as well as scientific meteorological simulations, genomics, computational physics, financial transactions and social network services generate a vast amount of data (Big Data). As a result it is estimated that digital data, which need to be processed and stored in data centres, will reach the zettabyte level before 2020. Time-sensitive Big data analysis and processing at high-performance computing infrastructures and by huge inter/intra data exchanges on data centres, becomes crucial and is a topic that attracts significant attention lately. The size of data-sets feasible to be processed in a reasonable amount of time is not only determined by the available processing capability but also by the bandwidth and the latency of the interconnecting network.

These new requirements, pose a serious challenge on the data-center and network operators who have to come up with a flexible and reliable solution, while considering the operational benefits that can result potentially for them. Novel photonic/plasmonic technologies as well as advanced optical networking approaches, may offer the capability of transmitting and processing of such big data with low power consumption, low latency and high level of flexibility, at relatively low costs. This tutorial discusses the impact of big data on the underlying network infrastructure with a particular focus on how novel photonic technologies and optical networking approaches in the high-performance computing (HPC), datacentre networks (DCN) and telecommunication networks can (TCN) be utilized to face the new requirements. The new infrastructure requirements in the big data era will be outlined. Then a brief presentation on the roadmap of new optical technologies that will be introduced in HPC, DCNs and TCNs in order – o improve their performance will be made. Finally in the third part of the tutorial, which will be the main focus, we will shift the discussion towards advanced networking solutions that enable flexibility, virtualization, application awareness and QoS support, thus making the network infrastructure more suitable for the new requirements.

This paper provides an overview of the Internet of Things (IoT) with emphasis on enabling technologies, protocols and application issues. The IoT is enabled by the latest developments in RFID, smart sensors, communication technologies and Internet protocols. The basic premise is to have smart sensors collaborate  directly without human involvement to deliver a new class of applications. The current revolution in Internet, mobile and machine-to-machine (M2M) technologies can be seen as the first phase of the IoT. In the coming years, the IoT is expected to bridge diverse technologies to enable new applications by connecting physical objects together in support of intelligent decision making. This paper starts by providing a horizontal overview of the IoT. Then, we give an overview of some technical details that pertain to the IoT enabling technologies, protocols and applications.

Compared to other survey papers in the field, our objective is to provide a more thorough summary of the most relevant protocols and application issues to enable researchers and application developers to get up to speed quickly on how the different protocols fit together to deliver desired functionalities without having to go through RFCs and the standards specifications. We also provide an overview of some of the key IoT challenges presented in the recent literature and provide a summary of related research work. Moreover, we explore the relation between the IoT and other emerging technologies including big data analytics and cloud and fog computing. We also present the need for better horizontal integration among IoT services. Finally, we present detailed service use-cases to illustrate how the different protocols presented in the paper fit together to deliver desired IoT services.

Mobile multi machine work environments, in general, consist of varying types of machines driving across a site to complete a moving or manipulation task. As the view from the machines over the environment can be limited due to the structure of the machines, the environment, and the moved/manipulated items, there is a risk of collision between machines. In this paper, we propose a situation awareness system aimed as a driver/operator assistive system to enhance the safety and efficiency of multi machine work environments. The system consists of the pose estimation of the machines, the M2M communication based on IEEE 802.11p, the future pose prediction of the machines, and a graphical user interface.

The system is designed to be general enough to be applicable in diverse work environments, which is most easily implemented as a retrofit for existing machines. In this paper, the implementation of the system presented is a proof of concept, and the focus is on how the overall system works in a real harbor environment during operation, ultimately aiming for the collision avoidance of harbor machines. The field tests show promising results, particularly regarding the applicability of the M2M communication technology in a very challenging and uncertain harbor environment.

Fog Computing is a recent computing paradigm that is extending cloud computing towards the edge of network. Due to its proximity to end-users, dense geographical distribution, open platform and support for high mobility, Fog Computing platforms can provide services with reduced latency and improved QoS. Thus it is becoming an important enabler for consumer centric Internet of Things based applications and services that require real time operations e.g. connected vehicles, smart road intersection management and smart grid.

The paper discusses one such architecture for connected vehicles with Road Side Units (RSUs) and M2M gateways including the Fog Computing Platform. M2Mdata processing with semantics, discovery and management of connected vehicles are briefly discussed as consumer centric IoT services enabled by the distinct characteristics of Fog Computing.

The current wireless cellular networks can be used to provide machine-to-machine (M2M) communication services. However, the Long Term Evolution (LTE) networks, which are designed for human users, may not be able to handle a large number of bursty random access requests from machine-type communication (MTC) devices. In this paper, we propose a scheme that uses both access class barring (ACB) and timing advance information to prevent random access overload inM2M systems. We formulate an optimization problem to determine the optimal ACB parameter, which maximizes the expected number of MTC devices successfully served in each random access slot. Hence, the number of random access slots required to serve all MTC devices can be minimized.

To reduce the computational complexity and improve the practicability of the proposed scheme, we propose a closed-form approximate solution to the optimization problem and present an algorithm to estimate the number of active MTC devices requiring access in each random access slot. The correctness of the analytical model and the accuracy of the estimation algorithm are validated via simulations. Results show that both numerical and approximate solutions provide the same performance. Our proposed scheme can reduce nearly half of the random access slots required to serve all MTC devices compared to the existing schemes, which use timing advance information only, ACB only, or cooperative ACB.

In this paper, we compare performance of fixed-grid Wavelength Division Multiplexing (WDM) and Elastic Optical Networks (EONs) in dynamic provisioning of many-to-many (m2m) flows. Currently, with a growth of services relying on many-to-many communication paradigm such as distributed computing, inter-Data Center communication, content delivery networking or other requiring high-bandwidth in group communication, it is vital to deliver new solutions facilitating these demanding transmissions.

Therefore, the authors investigate provisioning of m2m traffic in high-performance optical networks. This work focuses on dynamic Routing and Wavelength Assignment (RWA) problem in WDM networks as well as Routing and Spectrum Allocation (RSA) problem in EONs for m2m flows using replicated communication through auxiliary rendezvous servers.

The tremendous growth of machine-to-machine (M2M) applications has been a great attractor to cellular network operators to provide machine-type communication services. One of the important challenges for cellular systems supporting M2M terminals is coverage, because terminals can be located in spaces in buildings and structures suffering from significant penetration losses. Since these terminals are also often stationary, they are permanently without cellular coverage .

To address this critical issue, the third generation partnership project (3GPP), and in particular its radio access network technical specification group, commenced work on coverage enhancement (CE) for long-term evolution (LTE) systems in June 2013. This article reviews the CE objectives defined for LTE machine-type communication and presents CE methods for LTE down-link and up-link channels discussed in this group. The presented methods achieve CE in a spectrally efficient manner and without notably affecting performance for legacy (non- M2M) devices.