Showing papers in "Journal of Computer Networks and Communications in 2016"

An Overview on SDN Architectures with Multiple Controllers

Abstract: Software-defined networking offers several benefits for networking by separating the control plane from the data plane. However, networks’ scalability, reliability, and availability remain as a big issue. Accordingly, multicontroller architectures are important for SDN-enabled networks. This paper gives a comprehensive overview of SDN multicontroller architectures. It presents SDN and its main instantiation OpenFlow. Then, it explains in detail the differences between multiple types of multicontroller architectures, like the distribution method and the communication system. Furthermore, it provides already implemented and under research examples of multicontroller architectures by describing their design, their communication process, and their performance results.

Human Depth Sensors-Based Activity Recognition Using Spatiotemporal Features and Hidden Markov Model for Smart Environments

Abstract: Nowadays, advancements in depth imaging technologies have made human activity recognition HAR reliable without attaching optical markers or any other motion sensors to human body parts. This study presents a depth imaging-based HAR system to monitor and recognize human activities. In this work, we proposed spatiotemporal features approach to detect, track, and recognize human silhouettes using a sequence of RGB-D images. Under our proposed HAR framework, the required procedure includes detection of human depth silhouettes from the raw depth image sequence, removing background noise, and tracking of human silhouettes using frame differentiation constraints of human motion information. These depth silhouettes extract the spatiotemporal features based on depth sequential history, motion identification, optical flow, and joints information. Then, these features are processed by principal component analysis for dimension reduction and better feature representation. Finally, these optimal features are trained and they recognized activity using hidden Markov model. During experimental results, we demonstrate our proposed approach on three challenging depth videos datasets including IM-DailyDepthActivity, MSRAction3D, and MSRDailyActivity3D. All experimental results show the superiority of the proposed approach over the state-of-the-art methods.

On Internet Traffic Classification

Abstract: Traffic classification utilizing flow measurement enables operators to perform essential network management. Flow accounting methods such as NetFlow are, however, considered inadequate for classification requiring additional packet-level information, host behaviour analysis, and specialized hardware limiting their practical adoption. This paper aims to overcome these challenges by proposing two-phased machine learning classification mechanism with NetFlow as input. The individual flow classes are derived per application through k-means and are further used to train a C5.0 decision tree classifier. As part of validation, the initial unsupervised phase used flow records of fifteen popular Internet applications that were collected and independently subjected to k-means clustering to determine unique flow classes generated per application. The derived flow classes were afterwards used to train and test a supervised C5.0 based decision tree. The resulting classifier reported an average accuracy of 92.37% on approximately 3.4 million test cases increasing to 96.67% with adaptive boosting. The classifier specificity factor which accounted for differentiating content specific from supplementary flows ranged between 98.37% and 99.57%. Furthermore, the computational performance and accuracy of the proposed methodology in comparison with similar machine learning techniques lead us to recommend its extension to other applications in achieving highly granular real-time traffic classification.

A Data Mining Classification Approach for Behavioral Malware Detection

Abstract: Data mining techniques have numerous applications in malware detection. Classification method is one of the most popular data mining techniques. In this paper we present a data mining classification approach to detect malware behavior. We proposed different classification methods in order to detect malware based on the feature and behavior of each malware. A dynamic analysis method has been presented for identifying the malware features. A suggested program has been presented for converting a malware behavior executive history XML file to a suitable WEKA tool input. To illustrate the performance efficiency as well as training data and test, we apply the proposed approaches to a real case study data set using WEKA tool. The evaluation results demonstrated the availability of the proposed data mining approach. Also our proposed data mining approach is more efficient for detecting malware and behavioral classification of malware can be useful to detect malware in a behavioral antivirus.

Game-theory-based approach for energy routing in a smart grid network

Abstract: Small power plants and buildings with renewable power generation capability have recently been added to traditional central power plants. Through these facilities, prosumers appear to have a concurrent role in both energy production and consumption. Based on bidirectional power transfers by large numbers of prosumers, a smart microgrid has become an important factor in efficiently controlling the microgrids used in power markets and in conducting effective power trades among grids. In this paper, we present an approach utilizing the game theory for effective and efficient energy routing, which is a novel and challenging procedure for a smart microgrid network. First, we propose strategies for choosing the desired transaction price for both electricity surpluses and shortages to maximize profits through energy transactions. An optimization scheme is utilized to search for an energy route with minimum cost using the solving method used in a traditional transportation problem by treating the sale and purchase quantities as transportation supply and demand, respectively. To evaluate the effect of the proposed decision strategies, we simulated our mechanism, and the results proved that our mechanism yields results pursued by each strategy. Our proposed strategies will contribute to spreading a smart microgrid for enhancing the utilization of microgrids.

Developing an On-Demand Cloud-Based Sensing-as-a-Service System for Internet of Things

Abstract: The increasing number of Internet of Things (IoT) devices with various sensors has resulted in a focus on Cloud-based sensing-as-a-service (CSaaS) as a new value-added service, for example, providing temperature-sensing data via a cloud computing system. However, the industry encounters various challenges in the dynamic provisioning of on-demand CSaaS on diverse sensor networks. We require a system that will provide users with standardized access to various sensor networks and a level of abstraction that hides the underlying complexity. In this study, we aim to develop a cloud-based solution to address the challenges mentioned earlier. Our solution, SenseCloud, includes a sensor virtualization mechanism that interfaces with diverse sensor networks, a multitenancy mechanism that grants multiple users access to virtualized sensor networks while sharing the same underlying infrastructure, and a dynamic provisioning mechanism to allow the users to leverage the vast pool of resources on demand and on a pay-per-use basis. We implement a prototype of SenseCloud by using real sensors and verify the feasibility of our system and its performance. SenseCloud bridges the gap between sensor providers and sensor data consumers who wish to utilize sensor data.

Creating Values out of Internet of Things

Abstract: Internet of Things based cloud is envisaged to extract values other than the specified purpose for which it is to be utilized. It is hereby apprehended that different genre of values, rather business values, could efficiently be assimilated from the Internet of Things cloud platforms. It is also investigated to identify numerous domains of applications that are currently being associated with the similar cloud platforms. A case study on various types of value generation methods has been performed. A novel Internet of Things cloud stack is proposed to disseminate and aggregate the business values. Few research challenges are observed that shall need appropriate indulgence to generate more business values out of Internet of Things based cloud. This paper also seeks few research and industry related problems that need to be resolved. It further recommends several key parameters to the enterprise and government policymakers that should immediately be dealt with for long-term success.

Wormhole Detection Based on Ordinal MDS Using RTT in Wireless Sensor Network

Abstract: In wireless communication, wormhole attack is a crucial threat that deteriorates the normal functionality of the network. Invasion of wormholes destroys the network topology completely. However, most of the existing solutions require special hardware or synchronized clock or long processing time to defend against long path wormhole attacks. In this work, we propose a wormhole detection method using range-based topology comparison that exploits the local neighbourhood subgraph. The Round Trip Time RTT for each node pair is gathered to generate neighbour information. Then, the network is reconstructed by ordinal Multidimensional Scaling MDS followed by a suspicion phase that enlists the suspected wormholes based on the spatial reconstruction. Iterative computation of MDS helps to visualize the topology changes and can localize the potential wormholes. Finally, a verification phase is used to remove falsely accused nodes and identify real adversaries. The novelty of our algorithm is that it can detect both short path and long path wormhole links. Extensive simulations are executed to demonstrate the efficacy of our approach compared to existing ones.

A Hybrid Energy Efficient Protocol for Mobile Ad Hoc Networks

Abstract: We proposed an energy conservation technique called Location Based Topology Control with Sleep Scheduling for ad hoc networks. It uses the feature of both topology control approach and power management approach. Like the topology control approach, it attempts to reduce the transmission power of a node, which is determined from its neighborhood location information. A node goes to sleep state based on the traffic condition as that of power management approach. In the proposed scheme, a node goes to sleep state only when its absence does not create local partition in its neighborhood. We preformed extensive simulation to compare the proposed scheme with existing ones. Simulation results show that the energy consumption is lower with increase in the network lifetime and higher throughput in the proposed scheme.

Reliable and Energy Efficient Protocol for MANET Multicasting

Abstract: A mobile ad hoc network (MANET) consists of a self-configured set of portable mobile nodes without any central infrastructure to regulate traffic in the network. These networks present problems such as lack of congestion control, reliability, and energy consumption. In this paper, we present a new model for MANET multicasting called Reliable and Energy Efficient Protocol Depending on Distance and Remaining Energy (REEDDRE). Our proposal is based on a tone system to provide more efficiency and better performance, and it combines solutions over the Medium Access Control (MAC) layer. The protocol consists of a new construction method for mobile nodes using a clustering approach that depends on distance and remaining energy to provide more stability and to reduce energy consumption. In addition, we propose an adjustment to the typical multicast flow by adding unicast links between clusters. We further present in our model a technique to provide more reliability based on a busy tone system (RMBTM) to reduce excessive control overhead caused by control packets in error recovery. We simulate our proposal using OPNET, and the results show enhancement in terms of reliability, packet delivery ratio (PDR), energy consumption, and throughput.

ZigBee’s Received Signal Strength and Latency Evaluation under Varying Environments

Abstract: Being self-configured, self-organized, and self-healing low power technology, ZigBee has obtained significant attention in last few years for achieving ubiquitous communication among various devices within a Personal Area Network (PAN). Even after a decade of its emergence, it has been well serving the communication needs of numerous modern applications belonging to multiple industries and is still a spotlight for the researchers working on certain aspects to enhance productivity along with a major cost reduction. Despite its robust communication nature, it heavily depends upon the context and is prone to the external effects that may cause a serious threat to prospective applications. This paper presents the novel experimental analysis conducted on real test beds to evaluate the impact of continuously changing communication environment on various parameters, for example, RSSI (Received Signal Strength Indicator) and latency in the presence of multiple obstacles that may lead to severe degradation in the overall performance. Eventually, we suggest a suitable frame size for ZigBee based on our results deduced from the experimental study.

Markov model-based energy efficiency spectrum sensing in Cognitive Radio Sensor Networks

Abstract: Cognitive Radio Sensor Network (CRSN), incorporating cognitive radio capability in wireless sensor networks, is a new paradigm of the next-generation sensor network. Sensor nodes are usually battery powered and hence have strict energy constraints. As a result, energy efficiency is also a very critical problem in the CRSN. In this paper, we focus on energy consumption because of spectrum sensing. Furthermore, we present an adaptive spectrum sensing time interval strategy, in which SUs can adjust the next spectrum sensing time interval according to the current spectrum sensing results (namely, channel status). In order to find an optimal spectrum sensing time interval, we introduce the Markov model. Then, we establish a Markov model-based mathematical modeling for analyzing the relationship between spectrum sensing time interval and prior spectrum sensing results. Finally, numerical results demonstrate that the proposed strategy with dynamic adaptive spectrum sensing time interval exceeded listen before talk (LBT) strategy which is widely used for traditional wireless sensor networks.

Vertical handover decision algorithm using ants' colonies for 4G heterogeneous wireless networks

Abstract: With the development of 4G mobile telecommunication systems, providing users with the convenience of a seamless continuous connection is not enough anymore. Users want to be connected through the best available network with the best quality of service. It is necessary to have a good decision-making algorithm which decides whether it is necessary to perform handoff to another network, the best network to vertically perform handoff to, and the right time to initiate the handover. This paper proposes a new approach in which mobile terminals (MTs) continuously analyze the network and keep a database of the best available networks. The concept is based on QoS aware ant colony built on the vertical handoff mechanism that uses an updated version of ants' colony optimization decision algorithm (ACO R ), the dynamic and static factors such as RSS, the cost of service, bandwidth, the velocity of MT, the power consumption and security, and the module for predicting the traveling distance within an IEEE 802.11 WLAN cell. Simulation results show that we can not only meet the individual needs of users in terms of QoS, but also improve the whole system performance by reducing the number of handover failures and unnecessary handover instances by up to 95%.

The improved overhearing backup AODV protocol in MANET

Abstract: Mobile ad hoc network (MANET) is one of the most widely used networks, which has attracted attentions, having features such as limited energy resources, limited bandwidth, and security weaknesses due to lack of a central infrastructure. Safe and suitable routing is one of the research aspects of MANET. In this paper, a proposed method, called M-AODV, which is a type of overhearing backup protocol, based on AODV, is presented. The simulation results of this protocol, applied by NS2 simulator, showed the improvement of packet delivery rate and reduction of overhead and delay. Moreover, to assess the security of the proposed protocol, we simulated M-AODV and AODV protocols under black hole and wormhole attacks, using no security solution. The results showed that M-AODV had been improved in terms of packet delivery ratio, and the delay had been reduced as well, but the amount of overhead had been increased.

Secure Multicast Routing Algorithm for Wireless Mesh Networks

Abstract: Multicast is an indispensable communication technique in wireless mesh network WMN. Many applications in WMN including multicast TV, audio and video conferencing, and multiplayer social gaming use multicast transmission. On the other hand, security in multicast transmissions is crucial, without which the network services are significantly disrupted. Existing secure routing protocols that address different active attacks are still vulnerable due to subtle nature of flaws in protocol design. Moreover, existing secure routing protocols assume that adversarial nodes cannot share an out-of-band communication channel which rules out the possibility of wormhole attack. In this paper, we propose SEMRAW SEcure Multicast Routing Algorithm for Wireless mesh network that is resistant against all known active threats including wormhole attack. SEMRAW employs digital signatures to prevent a malicious node from gaining illegitimate access to the message contents. Security of SEMRAW is evaluated using the simulation paradigm approach.

Review of Adaptive Cell Selection Techniques in LTE-Advanced Heterogeneous Networks

Abstract: Poor cell selection is the main challenge in Picocell PeNB deployment in Long Term Evolution- LTE- Advanced heterogeneous networks HetNets because it results in load imbalance and intercell interference. A selection technique based on cell range extension CRE has been proposed for LTE-Advanced HetNets to extend the coverage of PeNBs for load balancing. However, poor CRE bias setting in cell selection inhibits the attainment of desired cell splitting gains. By contrast, a cell selection technique based on adaptive bias is a more effective solution to traffic load balancing in terms of increasing data rate compared with static bias-based approaches. This paper reviews the use of adaptive cell selection in LTE-Advanced HetNets by highlighting the importance of cell load estimation. The general performances of different techniques for adaptive CRE-based cell selection are compared. Results reveal that the adaptive CRE bias of the resource block utilization ratio RBUR technique exhibits the highest cell-edge throughput. Moreover, more accurate cell load estimation is obtained in the extended RBUR adaptive CRE bias technique through constant bit rate CBR traffic, which further improved load balancing as against the estimation based on the number of user equipment UE. Finally, this paper presents suggestions for future research directions.

Joint Channel Assignment and Routing in Multiradio Multichannel Wireless Mesh Networks

Abstract: Multiradio wireless mesh network is a promising architecture that improves the network capacity by exploiting multiple radio channels concurrently. Channel assignment and routing are underlying challenges in multiradio architectures since both determine the traffic distribution over links and channels. The interdependency between channel assignments and routing promotes toward the joint solutions for efficient configurations. This paper presents an in-depth review of the joint approaches of channel assignment and routing in multiradio wireless mesh networks. First, the key design issues, modeling, and approaches are identified and discussed. Second, existing algorithms for joint channel assignment and routing are presented and classified based on the channel assignment types. Furthermore, the set of reconfiguration algorithms to adapt the network traffic dynamics is also discussed. Finally, the paper presents some multiradio practical implementations and test-beds and points out the future research directions.

The impact of noise models on capacity performance of distribution Broadband over Power Lines networks

Abstract: This paper considers broadband potential of distribution Broadband over Power Lines (BPL) networks when different well-known noise models of the BPL literature are applied. The contribution of this paper is twofold. First, the seven most representative and used noise models of the BPL literature are synopsized in this paper. With reference to this set, the broadband performance of a great number of distribution BPL topologies either Overhead (OV) or Underground (UN), either Medium-Voltage (MV) or Low-Voltage (LV), is investigated in terms of suitable capacity metrics. Second, based on the proposed capacity metrics, a comparative capacity analysis is performed among variouswell-validated noisemodels. Through the careful study of its results, it is demonstrated that during capacity computations of distribution BPL networks, the flat Additive White Gaussian Noise (FL noise model) can be comfortably assumed as an efficient noise model either in 3-30MHz or in 3-88MHz frequency range since its capacity differences with the other well-proven noise models are negligible.

Secure Mix-Zones for Privacy Protection of Road Network Location Based Services Users

Abstract: Privacy has been found to be the major impediment and hence the area to be worked out for the provision of Location Based Services in the wide sense. With the emergence of smart, easily portable, communicating devices, information acquisition is achieving new domains. The work presented here is an extension of the ongoing work towards achieving privacy for the present day emerging communication techniques. This work emphasizes one of the most effective real-time privacy enhancement techniques called Mix-Zones. In this paper, we have presented a model of a secure road network with Mix-Zones getting activated on the basis of spatial as well as temporal factors. The temporal factors are ascertained by the amount of traffic and its flow. The paper also discusses the importance of the number of Mix-Zones a user traverses and their mixing effectiveness. We have also shown here using our simulations which are required for the real-time treatment of the problem that the proposed transient Mix-Zones are part of a viable and robust solution towards the road network privacy protection of the communicating moving objects of the present scenario.

Replica node detection using enhanced Single Hop Detection with Clonal Selection algorithm in Mobile Wireless Sensor Networks

Abstract: Security of Mobile Wireless Sensor Networks is a vital challenge as the sensor nodes are deployed in unattended environment and they are prone to various attacks. One among them is the node replication attack. In this, the physically insecure nodes are acquired by the adversary to clone them by having the same identity of the captured node, and the adversary deploys an unpredictable number of replicas throughout the network. Hence replica node detection is an important challenge in Mobile Wireless Sensor Networks. Various replica node detection techniques have been proposed to detect these replica nodes. The semethods incur control overheads and the detection accuracy is low when the replica is selected as a witness node. This paper proposes to solve these issues by enhancing the Single Hop Detection (SHD) method using the Clonal Selection algorithm to detect the clones by selecting the appropriate witness nodes. The advantages of the proposed method include (i) increase in the detection ratio, (ii) decrease in the control overhead, and (iii) increase in throughput. The performance of the proposed work is measured using detection ratio, false detection ratio, packet delivery ratio, average delay, control overheads, and throughput. The implementation is done using ns-2 to exhibit the actuality of the proposed work.

A Persistent Structured Hierarchical Overlay Network to Counter Intentional Churn Attack

Abstract: The increased use of structured overlay network for a variety of applications has attracted a lot of attention from both research community and attackers. However, the structural constraints, open nature anybody can join and anybody may leave, and unreliability of its participant nodes significantly affect the performance of these applications and make it vulnerable to a variety of attacks such as eclipse, Sybil, and churn. One attack to compromise the service availability in overlay network is intentional churn join/leave attack, where a large number of malicious users will join and leave the overlay network so frequently that the entire structure collapses and becomes unavailable. The focus of this paper is to provide a new robust, efficient, and scalable hierarchical overlay architecture that will counter these attacks by providing a structure that can accommodate the fleeting behaviour of nodes without causing much structural inconsistencies. The performance evaluation showed that the proposed architecture has more failure resilience and self-organization as compared to chord based architecture. Experimental results have demonstrated that the effect of failures on an overlay is proportional to the size of failure.

Performance Analysis of Cooperative Spectrum Sensing under Guaranteed Throughput Constraints for Cognitive Radio Networks

Abstract: One of the main challenges in cognitive radio networks is the ability of secondary users to detect the primary user presence with high probability of detection. In previous research, optimizing cooperative sensing in cognitive radio networks is performed for either a targeted probability of detection or a false alarm. After setting one of the probabilities as an optimization constraint, the other is optimized. In this paper, a guaranteed constant throughput at the secondary users is introduced as a target while optimizing probability of detection for cooperative sensing. Both sensing time values and number of cooperated cognitive radio secondary users are investigated to maximize the probability of detection of primary user. AND and OR hard decision schemes are considered and compared with soft decision scheme which is weighted modified deflection coefficient scheme W-MDC. It is illustrated that cooperation of all users and utilizing full frames for sensing time will not provide maximum probability of detection. A tradeoff between performances of cognitive radio networks with and without optimization is presented. The effects of varying network sizes, normalized target throughput, maximum frame duration times, and received signal-to-noise ratio at the fusion center are investigated for different fusion rules.

Exact SER Analysis of DFrFT-Based QPSK OFDM System over Frequency Selective Rayleigh Fading Channel with CFO

Abstract: We present the exact symbol error rate (SER) expression for quadrature phase shift keying (QPSK) modulation in frequency selective Rayleigh fading channel for discrete fractional Fourier transform- (DFrFT-) based orthogonal frequency division multiplexing (OFDM) system in the presence of carrier frequency offset (CFO). The theoretical result is confirmed by means of Monte Carlo simulations. It is shown that the performance of the proposed system, at different values of the DFrFT angle parameter źź,ź is better than that of OFDM based on discrete Fourier transform.

Detecting and Mitigating Smart Insider Jamming Attacks in MANETs Using Reputation-Based Coalition Game

Abstract: Security in mobile ad hoc networks MANETs is challenging due to the ability of adversaries to gather necessary intelligence to launch insider jamming attacks. The solutions to prevent external attacks on MANET are not applicable for defense against insider jamming attacks. There is a need for a formal framework to characterize the information required by adversaries to launch insider jamming attacks. In this paper, we propose a novel reputation-based coalition game in MANETs to detect and mitigate insider jamming attacks. Since there is no centralized controller in MANETs, the nodes rely heavily on availability of transmission rates and a reputation for each individual node in the coalition to detect the presence of internal jamming node. The nodes will form a stable grand coalition in order to make a strategic security defense decision, maintain the grand coalition based on node reputation, and exclude any malicious node based on reputation value. Simulation results show that our approach provides a framework to quantify information needed by adversaries to launch insider attacks. The proposed approach will improve MANET’s defense against insider attacks, while also reducing incorrect classification of legitimate nodes as jammers.

Dynamic Clustering Algorithm for Tracking Targets with High and Variable Celerity ATHVC

Abstract: Target tracking with the wireless sensors networks is to detect and locate a target on its entire path through a region of interest. This application arouses interest in the world of research for its many fields of use. Wireless sensor networks, thanks to their versatility, can be used in many hostile and inaccessible to humans environments. However, with a limited energy, they cannot remain permanently active, which can significantly reduce their lifetime. The formation of a cluster network seems an effective mechanism to increase network lifetime. We propose to build optimal dynamic clusters on the target trajectory. For increasing energy efficiency, our algorithm integrates for the first time, to our knowledge, strategies to avoid overlapping clusters and a model to wake up the sensors, adapting to the context of targets with large and variable speed.

Performance Analysis of Reuse Distance in Cooperative Broadcasting

Abstract: Cooperative broadcasting is a promising technique for robust broadcast with low overhead and delay in mobile ad hoc networks. The technique is attractive for mission-oriented mobile communication, where a majority of the traffic is of broadcast nature. In cooperative broadcasting, all nodes simultaneously retransmit packets. The receiver utilizes cooperative diversity in the simultaneously received signals. The retransmissions continue until all nodes are reached. After the packet has traveled a specific number of hops out from the source, denoted as reuse distance, the source node transmits a new broadcast packet in the time slot used for the previous broadcast packet. If the reuse distance is too small, interference causes packet loss in intermediate nodes. In the literature, a reuse distance of three is common. With an analysis based on a realistic interference model and real terrain data, we show that a reuse distance of at least four is necessary to avoid packet loss in sparsely connected networks, especially for high spectral efficiencies. For frequency hopping, widely used in military systems, we propose a novel method. This method almost eliminates interference for a reuse distance of three, increasing the throughput by 33% compared to systems with a reuse distance of four.

Design and Implementation of a Chaotic Scheme in Additive White Gaussian Noise Channel

Abstract: A new chaotic scheme named Flipped Chaotic On-Off Keying (FCOOK) is proposed for binary transmission. In FCOOK, the low correlation value between the stationary signal and its mirrored version is utilized. Transmitted signal for binary 1 is a chaotic segment added to its time flipped (mirrored) version within one bit duration, while in binary 0, no transmission takes place within the same bit duration. The proposed scheme is compared with the standard chaotic systems: Differential Chaos Shift Keying (DCSK) and Correlation Delay Shift Keying (CDSK). The Bit Error Rate (BER) of FCOOK is studied analytically based on Gaussian approximation method. Results show that the BER performance of FCOOK outperforms DCSK and CDSK in AWGN channel environment and with various Eb/No levels. Additionally, FCOOK offers a double bit rate compared with the standard DCSK.

A Quantitative Risk Evaluation Model for Network Security Based on Body Temperature

Abstract: These days, in allusion to the traditional network security risk evaluation model, which have certain limitations for real-time, accuracy, characterization. This paper proposed a quantitative risk evaluation model for network security based on body temperature QREM-BT, which refers to the mechanism of biological immune system and the imbalance of immune system which can result in body temperature changes, firstly, through the r-contiguous bits nonconstant matching rate algorithm to improve the detection quality of detector and reduce missing rate or false detection rate. Then the dynamic evolution process of the detector was described in detail. And the mechanism of increased antibody concentration, which is made up of activating mature detector and cloning memory detector, is mainly used to assess network risk caused by various species of attacks. Based on these reasons, this paper not only established the equation of antibody concentration increase factor but also put forward the antibody concentration quantitative calculation model. Finally, because the mechanism of antibody concentration change is reasonable and effective, which can effectively reflect the network risk, thus body temperature evaluation model was established in this paper. The simulation results showed that, according to body temperature value, the proposed model has more effective, real time to assess network security risk.

An Architecture for Anonymous Mobile Coupons in a Large Network

Abstract: A mobile coupon m-coupon can be presented with a smartphone for obtaining a financial discount when purchasing a product or a service. M-coupons are a powerful marketing tool that has enjoyed a huge growth and diffusion, involving tens of millions of people each year. We propose an architecture which may enable significant improvements over current m-coupon technology, in terms of acceptance of potential customers and of marketing actions that become feasible: the customer does not need to install any dedicated app; an m-coupon is not bound to any specific device or customer; an m-coupon may be redeemed at any store in a set of potentially many thousands of stores, without any prior arrangement between customer and store. We are not aware of any proposal with these properties.

Taking Binary Error Rate into Account to Improve OLSR Protocol

Abstract: This paper presents BER-OLSR, an enhanced OLSR protocol. We modify OLSR standard route choice and Multi-Point Relays (MPR) selection processes. Particularly, our new protocol takes into account Bit Error Rate (BER) of links during MPR selection and routing table calculation. MPR set of a node is populated so that access to each 2-hop-neighbor is ensured by the best path in terms of BER. For routing table calculation, lowest BER is privileged over lowest number of hops. Performances of this protocol are evaluated by simulation with realistic propagation and mobility models. We show that this new approach of OLSR routing protocol provides better packet delivery ratio and delay than the original OLSR algorithm, even in unfavorable conditions such as mobility or several interfering communications.