Enhancement of Return Routability Mechanism for Optimized‐NEMO Using Correspondent Firewall

Network Mobility (NEMO) handles mobility of multiple nodes in an aggregate manner as a mobile network. The standard NEMO suffers from a number of limitations, such as inefficient routing and increased handoff latency. Most previous studies attempting to solve such problems have imposed an extra signaling load and/or modified the functionalities of the main entities. In this paper, we propose a more secure and lightweight route optimization (RO) mechanism based on exploiting the firewall in performing the RO services on behalf of the correspondent nodes (CNs). The proposed mechanism provides secure communications by making an authorized decision about the mobile router (MR) home of address, MR care of address, and the complete mobile network prefixes underneath the MR. In addition, it reduces the total signaling required for NEMO handoffs, especially when the number of mobile network nodes and/or CNs is increased. Moreover, our proposed mechanism can be easily deployed without modifying the mobility protocol stack of CNs. A thorough analytical model and network simulator (Ns‐2) are used for evaluating the performance of the proposed mechanism compared with NEMO basic support protocol and state‐of‐the‐art RO schemes. Numerical and simulation results demonstrate that our proposed mechanism outperforms other RO schemes in terms of handoff latency and total signaling load on wired and wireless links.     

A Low-Voltage Fully Differential Pure Current Mode Current Operational Amplifier

In this paper a novel high-frequency fully differential pure current mode current operational amplifier (COA) is proposed that is, to the authors’ knowledge, the first pure MOSFET Current Mode Logic (MCML) COA in the world, so far. Doing fully current mode signal processing and avoiding high impedance nodes in the signal path grant the proposed COA such outstanding properties as high current gain, broad bandwidth, and low voltage and low-power consumption. The principle operation of the block is discussed and its outstanding properties are verified by HSPICE simulations using TSMC \(0.18\,\upmu \hbox {m}\) CMOS technology parameters. Pre-layout and Post-layout both plus Monte Carlo simulations are performed under supply voltages of \(\pm 0.75\,\hbox {V}\) to investigate its robust performance at the presence of fabrication non-idealities. The pre-layout plus Monte Carlo results are as; 93 dB current gain, \(8.2\,\hbox {MHz}\,\, f_{-3\,\text {dB}}, 89^{\circ }\) phase margin, 137 dB CMRR, 13 \(\Omega \) input impedance, \(89\,\hbox {M}\Omega \) output impedance and 1.37 mW consumed power. Also post-layout plus Monte Carlo simulation results (that are generally believed to be as reliable and practical as are measuring ones) are extracted that favorably show(in abovementioned order of pre-layout) 88 dB current gain, \(6.9\,\hbox {MHz} f_{-3\text {db}} , 131^{\circ }\) phase margin and 96 dB CMRR, \(22\,\Omega \) input impedance, \(33\,\hbox {M}\Omega \) output impedance and only 1.43 mW consumed power. These results altogether prove both excellent quality and well resistance of the proposed COA against technology and fabrication non-idealities.     

Efficient Computation Offloading Decision in Mobile Cloud Computing over 5G Network

Due to the significant advancement of Smartphone technology, the applications targeted for these devices are getting more and more complex and demanding of high power and resources. Mobile cloud computing (MCC) allows the Smart phones to perform these highly demanding tasks with the help of powerful cloud servers. However, to decide whether a given part of an application is cost-effective to execute in local mobile device or in the cloud server is a difficult problem in MCC. It is due to the trade-off between saving energy consumption while maintaining the strict latency requirements of applications. Currently, 5th generation mobile network (5G) is getting much attention, which can support increased network capacity, high data rate and low latency and can pave the way for solving the computation offloading problem in MCC. In this paper, we design an intelligent computation offloading system that takes tradeoff decisions for code offloading from a mobile device to cloud server over the 5G network. We develop a metric for tradeoff decision making that can maximize energy saving while maintain strict latency requirements of user applications in the 5G system. We evaluate the performances of the proposed system in a test-bed implementation, and the results show that it outperforms the state-of-the-art methods in terms of accuracy, computation and energy saving.     

RoBiN: Random Access using Border Routers in Cellular Networks

Introducing Machine-to-Machine (M2M) communications over traditional 4G cellular networks make the cellular random access channel more congested and collision-prone. In order to resolve this random access congestion, we propose RoBiN - Random access using Border router in M2M cellular Networks. RoBiN proposes an architectural modification of introducing small cells, called Border Routers (BR), in cellular networks, with complete frequency reuse capability. We formulate the aforementioned challenge in terms of collision probability and system capacity. Subsequently, we propose an efficient solution for M2M communications in cellular networks. Exhaustive mathematical analysis shows that RoBiN significantly improves the random access success probability, by 50 % over existing 4G cellular systems. Simulation results on typical 4G networks corroborate our mathematical analysis and demonstrate almost 15 dB increase in Signal-to-Interference-plus-Noise Ratio (SINR) and 3 times throughput improvements over legacy 4G cellular systems. Furthermore, RoBiN also achieves 50 %?80 % improvement in collision probability over existing time alignment matching work.     

Combining replication and checkpointing redundancies for reducing resiliency overhead

We herein propose a heuristic redundancy selection algorithm that combines resubmission, replication, and checkpointing redundancies to reduce the resiliency overhead in fault‐tolerant workflow scheduling. The appropriate combination of these redundancies for workflow tasks is obtained in two consecutive phases. First, to compute the replication vector (number of task replicas), we apportion the set of provisioned resources among concurrently executing tasks according to their needs. Subsequently, we obtain the optimal checkpointing interval for each task as a function of the number of replicas and characteristics of tasks and computational environment. We formulate the problem of obtaining the optimal checkpointing interval for replicated tasks in situations where checkpoint files can be exchanged among computational resources. The results of our simulation experiments, on both randomly generated workflow graphs and real‐world applications, demonstrated that both the proposed replication vector computation algorithm and the proposed checkpointing scheme reduced the resiliency overhead.     

Fingerprinting Based Indoor Localization Considering the Dynamic Nature of Wi-Fi Signals

Current localization techniques in outdoors cannot work well in indoors. Wi-Fi fingerprinting technique is an emerging localization technique for indoor environments. However in this technique, the dynamic nature of WiFi signals affects the accuracy of the measurements. In this paper, we use affinity propagation clustering method to decrease the computation complexity in location estimation. Then, we use the least variance of Received Signal Strength (RSS) measured among Access Points (APs) in each cluster. Also we assign lower weights to altering APs for each point in a cluster, to represent the level of similarity to Test Point (TP) by considering the dynamic nature of signals in indoor environments. A method for updating the radio map and improving the results is then proposed to decrease the cost of constructing the radio map. Simulation results show that the proposed method has 22.5% improvement in average in localization results, considering one altering AP in the layout, compared to the case when only RSS subset sampling is considered for localization because of altering APs.

     

Sink-oriented tree based data dissemination protocol for mobile sinks wireless sensor networks

Wireless Networks - Data dissemination toward static sinks causes the nearby nodes to deplete their energy quicker than the other nodes in the field (i.e., this is referred to as the hotspot...     

Optimal Resource Allocation in Heterogeneous MIMO Cognitive Radio Networks

The optimal resource allocation in MIMO cognitive radio networks with heterogeneous secondary users, centralized and distributed users, is investigated in this work. The core aim of this work is to study the joint problems of transmission time and power allocation in a MIMO cognitive radio scenario. The optimization objective is to maximize the total capacity of the secondary users (SUs) with the constraint of fairness. At first, the joint problems of transmission time and power allocation for centralized SUs in uplink is optimized. Afterwards, for the heterogeneous case with both the centralized and distributed secondary users, the resource allocation problem is formulated and an iterative power water-filling scheme is proposed to achieve the optimal resource allocation for both kinds of SUs. A dynamic optimal joint transmission time and power allocation scheme for heterogeneous cognitive radio networks is proposed. The simulation results illustrate the performance of the proposed scheme and its superiority over other power control schemes.