Network Deployment Strategies Research Articles

The effect of service rollout on demand forecasting: The application of modified Bass model to the step growing markets

The purpose of this research is to develop a new forecasting model for gradual development of telecommunications network infrastructure. If technical support service is not provided in the whole territory, then the service cannot be simultaneously offered to the market. Therefore, the adoption process is performing in steps, following the systematic process of the infrastructure development. We propose the step growing market model with variable market potential, based on the fundamental Bass diffusion model. This model uses market segmentation and the simulation of various market scenarios in order to indicate effective service rollout. Demand forecasting is required in order to dimensioning of required network resources. Moreover, this model offers the insight into the operator's compromises regarding decisions in the network investment. The resulting plan is a network deployment strategy that defines temporal sequence of network layouts. Thus, the upgrade plan indicates which investments are indispensible at each point of time.

Joint Design of Radio and Transport for Green Residential Access Networks

Mobile networks are the largest contributor to the carbon footprint of the telecom sector and their contribution is expected to rapidly increase in the future due to the foreseen traffic growth. Therefore, there is an increasing urgency in the definition of green mobile network deployment strategies. This paper proposes a four-step design and power assessment methodology for mobile networks, taking into consideration both radio and transport segments. A number of mobile network deployment architectures for urban residential areas based on different radio (i.e., macro base station, distributed indoor radio, femto cell) and transport (i.e., microwave, copper, optical fiber) technologies are proposed and evaluated to identify the most energy efficient solution. The results show that with low traffic the conventional macro base station deployment with microwave based backhaul is the best option. However, with higher traffic values heterogeneous networks with macro base stations and indoor small cells are more energy efficient. The best small cell solution highly depends on the transport network architecture. In particular, our results show that a femto cell based deployment with optical fiber backhaul is the most energy efficient, even if a distributed indoor radio architecture (DRA) deployment with fiber fronthaul is also a competitive approach.

STEM-NET: How to deploy a self-organizing network of mobile end-user devices for emergency communication

Spontaneous wireless networks constructed out of mobile end-user devices (e.g. smartphones or tablets) are currently receiving considerable interest as they enable a wide range of novel, highly pervasive and user-centric network services and applications. In this paper, we focus on emergency-related scenarios, and we investigate the potential of spontaneous networks for providing Internet connectivity over the emergency area through the sharing of resources owned by the end-user devices. Novel and extremely flexible network deployment strategies are required in order to cope with the user mobility, the limited communication capabilities of wireless devices, and the intrinsic dynamics of traffic loads and QoS requirements. To this purpose, we propose here a novel approach toward the deployment of spontaneous networks composed by a new generation of wireless devices – called Stem Nodes (SNs) – to emphasize their ability to cover multiple network roles (e.g. gateway, router). The self-organization of the spontaneous network is then achieved through the local reconfiguration of each SN. Two complementary research contributions are provided. First, we describe the software architecture of a SN (which can be implemented on top of existing end-user devices), and we detail how a SN can manage its role set, eventually extending it through cooperation with other SNs. Second, we propose distributed algorithms, based on swarm intelligence principles, through which each SN can autonomously select its role, and self-elect to gateway or router, so that end-to-end performance are maximized while the lifetime of the spontaneous emergency network is prolonged. The ability of the proposed algorithm to guarantee adaptive and self-organizing network behaviors is demonstrated through extensive Omnet++ simulations, and through a prototype implementation of the SN architecture on a real testbed.

Energy-efficient non-cooperative cognitive radio networks: micro, meso, and macro views

Cognitive radio technology can significantly improve spectrum utilization efficiency via enabling secondary users to access licensed spectrum dynamically without harmful interference to primary users. Most existing works on cognitive radio networks were focused on enhancing spectrum efficiency using spectrum sensing, spectrum sharing, and network deployment schemes. However, the energy efficiency issue was largely ignored. Thus, the dilemma between high energy consumption by fast-growing wireless communications and fewer global energy resources has motivated research on energy-efficient cognitive radio networks for enhancing spectrum efficiency and energy efficiency simultaneously. In this article, we overview energy-efficient non-cooperative cognitive radio networks from the micro, meso, and macro perspectives, where the micro view means how to design energy-efficient spectrum sensing algorithms for each individual secondary user, the meso view means how to coordinate non-cooperative secondary users to share spectrum efficiently, and the macro view means how to deploy cognitive radio networks in an energy-efficient approach.

Self organising cloud cells: a resource efficient network densification strategy

AbstractNetwork densification is envisioned as the key enabler for 2020 vision that requires cellular systems to grow in capacity by hundreds of times to cope with unprecedented traffic growth trends being witnessed since advent of broadband on the move. However, increased energy consumption and complex mobility management associated with network densifications remain as the two main challenges to be addressed before further network densification can be exploited on a wide scale. In the wake of these challenges, this paper proposes and evaluates a novel dense network deployment strategy for increasing the capacity of future cellular systems without sacrificing energy efficiency and compromising mobility performance. Our deployment architecture consists of smart small cells, called cloud nodes, which provide data coverage to individual users on a demand bases while taking into account the spatial and temporal dynamics of user mobility and traffic. The decision to activate the cloud nodes, such that certain performance objectives at system level are targeted, is carried out by the overlaying macrocell based on a fuzzy‐logic framework. We also compare the proposed architecture with conventional macrocell only deployment and pure microcell‐based dense deployment in terms of blocking probability, handover probability and energy efficiency and discuss and quantify the trade‐offs therein.© 2014 The Authors. Transactions on Emerging Telecommunications Technologies published by John Wiley & Sons, Ltd.

Cost Modelling and Studies with Different Deployment Strategies for Wireless Multimedia Sensor Network Over Flat and Elevated Terrains

Wireless multimedia sensor networks (WMSNs) is widely used for surveillance application. These multimedia (audio and video) nodes are distributed according to different deployment strategies in a multi-tier heterogeneous architecture environment. In this paper we have modelled the deployment cost of WMSN considering the sensor type (audio or video), sensor configuration such as remaining energy of battery, deployment point, and terrain characteristics for surveillance applications. Using our proposed cost models we have studied the effects of different deployment strategies of WMSN over flat and elevated terrains. Our cost models helps in minimizing the cost of deployment while maintaining Quality-of-Service i.e., the coverage and connectivity of the audio and video sensors separately. We have formulated an integer linear program and proposed a heuristic solution to minimize the placement costs subject to network coverage requirements using our first cost model. Our second cost model is used to propose a scheme that will ensure connectivity of the network. We have done simulations with three network deployment strategies, namely deterministic, random and hybrid and show that the hybrid deployment of sensor nodes yields a balance of performance and cost as compared to the other two. Our study provides guidelines for the network architect to select a particular deployment strategy under performance and cost requirements.

Energy consumption of radio access networks in Finland

Energy consumption of radio access networks is related to the speed and volume of mobile data traffic. Finland aims to achieve two conflicting targets by 2015, the one of 100 Mbps user data rate provision to nearly all citizens and the other of the reduction of Information and Communications Technology industry carbon footprint. The purpose of this paper is to evaluate the energy consumption for several radio access networks deployment scenarios. Mobile operators can advance energy efficiency through (1) energy optimization of individual sites and (2) choice of energy efficient network deployment strategies. Models for the site power consumption, the average site traffic load factor and the average subscription mobile data traffic, are developed. The results show a reduction of energy consumption for mobile network based on LTE radio access technology which operates at 1800 MHz in urban region and 800 MHz in suburban and rural regions. In the dense urban region the LTE base stations are installed on the existing sites and in the less-dense urban region, wide-to-local area offloading is required.

Impact of High Power Interference Sources in Planning and Deployment of Wireless Sensor Networks and Devices in the 2.4 GHz Frequency Band in Heterogeneous Environments

In this work, the impact of radiofrequency radiation leakage from microwave ovens and its effect on 802.15.4 ZigBee-compliant wireless sensor networks operating in the 2.4 GHz Industrial Scientific Medical (ISM) band is analyzed. By means of a novel radioplanning approach, based on electromagnetic field simulation of a microwave oven and determination of equivalent radiation sources applied to an in-house developed 3D ray launching algorithm, estimation of the microwave oven's power leakage is obtained for the complete volume of an indoor scenario. The magnitude and the variable nature of the interference is analyzed and the impact in the radio link quality in operating wireless sensors is estimated and compared with radio channel measurements as well as packet measurements. The measurement results reveal the importance of selecting an adequate 802.15.4 channel, as well as the Wireless Sensor Network deployment strategy within this type of environment, in order to optimize energy consumption and increase the overall network performance. The proposed method enables one to estimate potential interference effects in devices operating within the 2.4 GHz band in the complete scenario, prior to wireless sensor network deployment, which can aid in achieving the most optimal network topology.

Deployment Strategies and Energy Efficiency of Cellular Networks

The energy efficiency of cellular networks is explored for different network deployment strategies and traffic conditions. The total network power consumption and the ratios Watts/kbps, Watts/user are used as metrics to quantify the performance and it is shown that efficiency depends on the deployment strategy and the state of operation of the network (underutilized-overutilized). As a general conclusion it is shown that a microcell based network, comprising a large number of low power stations, is the most efficient strategy but it does not present traffic proportional characteristics. For the purpose of the investigation, the paper presents a pre-processing of the database 3D ray tracing algorithm that is enhanced with an image test procedure and multiple slope diffraction mechanisms to achieve fast and accurate predictions. The algorithm is used for channel estimations over a real urban environment described in a vector format. In addition, a power control algorithm is developed that explicitly considers power levels of neighbor base stations and is used for the network power consumption estimation. Finally, network planning is achieved through an evolutionary optimization technique that combines the above mentioned algorithms.

Conflicting Policies Lead to Disharmonic Convergence

Crafting coherent network deployment and development strategies across global political regimes with wildly divergent philosophies is growing more difficult. Some believe that the intertwining between technology deployment and amorphous public policy directions should be at the forefront of policy decision making, but developers and engineers will need to get on board, first.

General Network Lifetime and Cost Models for Evaluating Sensor Network Deployment Strategies

In multihop wireless sensor networks that are often characterized by many-to-one (convergecast) traffic patterns, problems related to energy imbalance among sensors often appear. Sensors closer to a data sink are usually required to forward a large amount of traffic for sensors farther from the data sink. Therefore, these sensors tend to die early, leaving areas of the network completely unmonitored and reducing the functional network lifetime. In our study, we explore possible sensor network deployment strategies that maximize sensor network lifetime by mitigating the problem of the hot spot around the data sink. Strategies such as variable-range transmission power control with optimal traffic distribution, mobile-data-sink deployment, multiple-data-sink deployment, nonuniform initial energy assignment, and intelligent sensor/relay deployment are investigated. We suggest a general model to analyze and evaluate these strategies. In this model, we not only discover how to maximize the network lifetime given certain network constraints but also consider the factor of extra costs involved in more complex deployment strategies. This paper presents a comprehensive analysis on the maximum achievable sensor network lifetime for different deployment strategies, and it also provides practical cost-efficient sensor network deployment guidelines.