The paper is devoted to neural modeling of link occupancy distribution. Multi-service (i.e., bandwidth sharing between different traffic classes) models of a single, possibly wireless transmission link for rigid, adaptive and elastic traffic are developed based on Markov reward models. Link occupancy distribution is introduced as embedded, discrete time Markov chain researched with vector quantization. Link occupancy performance is simulated as a combination of single queues with random distributions of arrival processes and holding times in service phases. Link occupancy probability density is determined using learning vector quantization in a two-layered neural structure. Simulation and numerical results are shown.
Software-Defined Networking (SDN) separates the control plane from the data plane to improve the control flexibility, supporting multiple services with their isolated physical resources. In SDN, the virtual network (VN) mapping is required by network services for allocating these resources in the multidomain SDN. Such mapping problem is challenged by the NP-Completeness of the mapping and business privacy to protect the domain topology. We propose a novel multi-domain mapping algorithm for SDN using a distributed architecture to achieve a better efficiency and flexibility than the traditional PolyViNE approach, meanwhile protecting the privacy. By simulating on a large synthesized topology with 10 to 40 domains, our approach shows 25% and 15% faster than the PolyViNE in time, and 30% better in balancing load on multiple controllers.
SUNSEED, “Sustainable and robust networking for smart electricity distribution”, is a 3-year project started in 2014 and partially funded under call FP7-ICT-2013-11. The project objective is to research, design and implement methods for exploitation of existing communication infrastructure of energy distribution service operators (DSO) and telecom operators (telco) for the future smart grid operations and services. To achieve this objective, SUNSEED proposes an evolutionary approach to converge existing DSO and telco networks, consisting of six steps: overlap, interconnect, interoperate, manage, plan and open. Each step involves identification of the related smart grid service requirements and implementation of the appropriate solutions. The promise of SUNSEED approach lies in potentially much lower investments and total cost of ownership of future smart energy grids within dense distributed energy generation and prosumer environments.
We consider a wiretap multiple-input multiple-output multiple-eavesdropper (MIMOME) channel, where agent Alice aims at transmitting a secret message to agent Bob, while leaking no information on it to an eavesdropper agent Eve. We assume that Alice has more antennas than both Bob and Eve, and that she has only statistical knowledge of the channel towards Eve. We focus on the low-noise regime, and assess the secrecy rates that are achievable when the secret message determines the distribution of a multivariate Gaussian mixture model (GMM) from which a realization is generated and transmitted over the channel. In particular, we show that if Eve has fewer antennas than Bob, secret transmission is always possible at low-noise. Moreover, we show that in the low-noise limit the secrecy capacity of our scheme coincides with its unconstrained capacity, by providing a class of covariance matrices that allow to attain such limit without the need of wiretap coding.
Sensors are the tiny nodes which are used for getting information from any particular area for some particular situations. These are usually deployed in such places where existence of human may not be possible. These are very small electronic devices having very short amount of resources like memory, power as well as bandwidth. A number of nodes are deployed which are connected with each other and also connected with a base station. While deploying on particular place, there might occur two types of problems; nodes may be in excess or very far from each other. If the nodes are in majority, then the network may be inefficient due to interference and malicious access control collisions. Efficiency of network is the main issue to be resolved at priority bases. While transferring of information from node to node or from node to base station, the least time must be consumed. As much as the network will be efficient, the data will be received and sent easily from node to node or at sink. For making network reliable and secure, cryptographic techniques have been used. A hybrid algorithm has been suggested here using both symmetric and asymmetric cryptographic techniques. A message is divided into two parts containing Meta data and original data. Symmetric cryptography has been implemented on Meta data part while asymmetric cryptography has been applied for the original part of message. This approach will make our network more efficient as well as secure and reliable.
EPIKOUROS is an innovative project where methodologies and tools will be developed for designing, building and deploying Internet-of-Things applications on Virtual Environments. EPIKOUROS main goal is to design and develop a virtualized middleware platform that would allow easily creating and structuring environments. In turn, it would allow the collection, management and integration of information generated by multiple sensors and sensor-networks, as well as the management of business process procedures that are supported by the sensors' infrastructure. The project will use as proof-of-concept scenarios from independent living, intelligent/multimodal transport and building management.
The integration of existing heterogeneous vertical M2M systems into a new horizontal platform has been recognized as a key factor to boost the development of the Internet of Things vision. In this scenario, the European project BETaaS (Building the Environment for the Things as a Service) aims at developing a framework to enable integration of different M2M systems exposing physical objects to applications through a novel service-oriented interface, the Things as a Service model. Quality of Service support is a non-functional requirement of paramount importance for applications with stringent requirements which has been included by design in the BETaaS platform. In this paper the negotiation framework adopted in BETaaS to allow Machine-to-Machine (M2M) applications to negotiate the required Service Level Agreement is presented. The goal is to expose to applications a standard interface which can be exploited to negotiate the desired QoS selecting one of the service classes defined by the platform.
One of the most important components of attitude determination system for small satellite is sun sensor. In this paper design, development and calibration of 2-axis digital sun sensor using linear Photodiodes array is presented. Senor design comprises two linear arrays mounted orthogonally to provide Sun aspect angle in two axes. The Sun aspect angle is determined by the centroid based technique and implemented using FPGA. The proposed centroid algorithm is capable of obtaining the position of the centroid to an accuracy of sub pixel level which is desirable in such designs. A method of calibration using natural sun light is also presented. Commercial grade components were used which have resulted in development of low cost, light weight and power efficient sensor.
Object Tracking based on Active Contour Modeling is an image processing based technology that uses snapshots of the object under consideration to track it via robot in the real world. The objective has been to implement a unique methodology that employs the pursuing and adapting of contour to the current state of image, and hence track the object. The system can be implemented in drone planes wherein this algorithm can be used to guide the movement of the gun based on the movements of the object, or, in robot games with a slightly more advanced robot. Initially Image Processing is performed to reduce operation complexity and achieve swift real-time performance. A set of contour-based modeling algorithms is then implemented to 'actively' track the subject. Also, relative transformation calculations are made to lock the target via robot, continuously. MATLAB is used to simulate and implement the system and it is tested on field with a ball placed on it and a robot tracking the ball. The experiments prove that the system successfully detects and tracks the object efficiently in the real world for all horizontal and vertical transitions.
The heterogeneous network (HetNet) architecture unprecedentedly reusing spectrum faces a critical challenge of interference mitigation among cells. For this goal, existing solutions successfully reaching resource orthogonality, however, impose critical assumptions of ubiquitous synchronization among all cells. Lacking of an effective network synchronization scheme, the installation of existing solutions is obstructed. This challenge motivates us to comprehensively study all-embracing solutions including two categories: synchronous and asynchronous based resource orthogonality schemes. In the first category, to be compatible with existing synchronous resource orthogonality techniques, we propose a series of timing alignment schemes by innovations of gossip algorithm and voter algorithm. In the second category, we avoid the synchronous framework to propose an asynchronous resource management inspired from game theory. The equally outstanding performance in both categories reveals an engineering duality on timing alignment and resource orthogonality, to provide foundations and design paradigm shifts toward the fifth generation (5G) HetNet.
In this paper, we complement the developed OFDM error floor prediction analysis and the corresponding Monte-Carlo simulations results by more comprehensive tests specifically referencing the LTE FDD downlink environment that is for this purpose simulated in controlled lab conditions using state-of-the-art industry-standard software simulation test tool. The validity of the model was confirmed by the achieved results that closely match the ones coming out of the earlier obtained model-specific and OFDM-basic Monte Carlo simulations.
In the cognitive radio networks, the spectrum handoff scheme directly determines the system performance. That's to say a handoff scheme that cannot fully uses the information of users and channels will not provide the best choice. In this paper, a spectrum handoff scheme based on comprehensive cost is proposed. By jointly computing multiple factors such as transmission delay, channel bandwidth, SNR and the characteristics of users and so on, we get a Judgment Matrix for channel selection so that we can give consideration to all these factors' influence on the final system performance. In this paper we also set up a cognitive radio scenario to simulate the process and verify our scheme. Comparing with the random access scheme, the simulation results show that our scheme can reduce the probability of spectrum handoff and enhance the throughput capacity significantly and finally result in larger service carrying capacity and lower service drop number.
In the sprouting paradigm of interoperable radio networks, wideband spectrum sensing is a challenging task for analog-to-digital converters (ADC) incorporated at the prevailing wireless radio systems because of the necessities of high sampling rates functioning at or above Nyquist frequencies. In order to cope with current ADCs, compressive sampling (CS), a promising scheme in signal processing arena, can be employed to search for the spectrum holes in the sparse wideband signals which are then opportunistically used by the cognitive radios (CR). In CS, transform coding as well as measurement matrix selection is an essential tool and it plays a vital role in the acquisition of wideband signals which comes out with a few number of random measurements. In this paper, two types of transform coding (Discrete Cosine Transform, DCT and Discrete Walsh-Hadamard Transform, WHT) is analyzed in the context of sparse wideband estimation via a well-known CS approach e.g., l 1 -norm optimization problem which could be used for spectrum sensing in wideband CR. Through the engagement of those measurement matrices, detection performance, execution time to sense PU bands and achievable capacity are investigated and analyzed at a single CR node. Finally, WHT coded CS scheme has been proposed for the wideband CR spectrum sensing as the simulation results arrange for the validation of our choice.
Current and new-generation wireless mobile networks face a high demand for very large bandwidth. Due to the high costs of spectrum usage and of the access network development, the network operators could be interested in sharing spectrum and operating costs of the access network. Already, Carrier aggregation, defined in 3GPP Rel. 10 allows a form of easy inter-operator sharing. The cloud computing paradigm will also most likely be extended to cover not only the delivery of computing resources over the Internet, but, in the case of mobile networks, also the delivery of Core Network functionalities to the Access Network, M2M and multimedia applications. The paper discusses the main technological pillars for future converged mobile networks and proposes an architecture reference model for cloud-based management and monitoring of the shared network resources and radio spectrum. The main technical and economic challenges that need to be addressed for this architecture to be deployed are also highlighted.
The goal of the Distributed beamforming (DB) method is to collaboratively forward the Cognitive Radio (CR) signal to the Distant CR (DCR) user. We propose a novel Nodes Selection (NS) method which is based on the differences in beam width of a broadside array and an end-fire array. In this scheme the CR nodes which are able to form a full size end-fire array and a reduced size broadside array are selected for forming the beam. The method chooses those CR nodes which are located in the “belt” area along the direction of the DCR user. Simulation results of the average beampattern of the method show that the main beams are successfully directed towards the DCR users and are enlarged for practical applications in CR networks. Furthermore, for a CR network with a large physical size, the proposed node selection method can widen the main beam while maintaining sufficiently low sidelobe levels for CR transmission.
With the rapid development of mobile Internet, numerous mobile services have become part of the people's life. Accordingly, the traffic rate generated by mobile devices are humongous and it is very hard to analyze its characteristics in traditional ways due to their scalability. This problem can be viewed as a big data problem and we develop a Hadoop-based system, Traffic Analysis System (TAS), to as the solution in this paper. Based on TAS, we analyze the real mobile Internet traffic data collected from a capital city in southern China. The analysis results illustrate the basic makeup of current mobile devices. In addition, it indicates that the users with different interests in different networks have quite different behaviors, which could provide important references for Internet service providers.
A two-way pricing mechanism is incorporated into the Stackelberg game to mitigate the co-tier interference by controlling the uplink transmit power. Specifically, by employing the pricing mechanism, leader femto base station (FBS) can get reward from follower femtocell user equipments (FUEs) and vice versa. All FBSs are assumed to operate under the co-channel mode, i.e., all FBSs use the same frequency band and every FBS is operated in the closed subscriber group (CSG) access mode. By assigning the maximum tolerable co-tier interference, the leader FBS protects itself by pricing the interference from follower FUEs. On the contrary, follower FUEs control the transmit power based on the pricing strategy of the leader. For different interference constraints, simulation results obtained by Matlab show that leader and followers can always compromise on a Stackel-berg equilibrium (SE) point where both leader and followers achieve the maximal utility. Hence, the proposed Stackelberg game with two-way pricing mechanism power control scheme provides a viable solution to mitigate co-tier interference in femtocell networks.
Internet of things (IoT) is an emerging paradigm where the devices around us (persistent and non-persistent) are connected to each other to provide seamless communication, and contextual services. In the IoT, each device cannot be authenticated in the short time due to unbounded number of devices. Equally, it is difficult to get receipt of their authentication request at the same time. Therefore, secure, and efficient group authentication scheme is required that authenticates a group of devices at once in the context of resource constrained IoT. This paper presents novel Threshold Cryptography-based Group Authentication (TCGA) scheme for the IoT which verifies authenticity of all the devices taking part in the group communication. The proposed TCGA scheme is implemented for WIFI environment, and the result shows that TCGA scheme is lightweight, and alleviates the effect of battery exhaustion attack. This paper also presents time analysis, and formal security analysis of TCGA scheme which shows that the proposed TCGA scheme is safe from the replay, man-in-the-middle attack, and is scalable in nature.
We consider the problem of intelligent spectrum sensing based on historical data in the context of Cognitive Wireless Sensor Networks with the goal to minimize the long term energy consumed for spectrum sensing. The problem involves a wireless sensor with cognitive abilities that must decide how often to sense a specific region of the spectrum based on the last known state of its primary user. We model the problem at hand as a pure-exploration multi-armed bandit problem with dependent arms and use two well known arm pulling strategies to tackle it. Next, we identify the existing correlation structure among the candidate solutions and utilize it to significantly speed up the learning process. Numerical results verify the effectiveness of the proposed strategies.
This work studies what effects a mixed service scenario would give on system capacity and fairness of the downlink of an OFDMA system using different types of resource allocation algorithms. It also contrasts fairness to opportunistic resource allocation among user groups. The study evaluates and compares the performance of the different types of resource allocation schemes in the downlink of OFDMA systems based on user fairness, spectral efficiency and delay. It divides users into inner and outer groups according to channel conditions to study fairness versus opportunism. From the MATLAB-based simulation results, it is shown that the proposed RRA algorithm, facilitates a fairer distribution of system resources between users than the system capacity maximization technique.
