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Proof-of-Work (PoW) blockchain systems like Bitcoin and Ethereum are vulnerable to selfholding attack. The prior modeling-based works about this attack only considered Bitcoin and assumed that there were at most two honest pools in a perfect network (no natural fork in such networks). However, a blockchain network is imperfect due to block propagation delay, which can lead to forking. Moreover, there may be more than two pools under attack. This paper aims for a quantitative analysis of an imperfect PoW blockchain network system under selfholding attack. We develop a novel stochastic model and derive formulas to evaluate the effect of selfholding attack on miner revenue, system security and system performance. Our work can be used to analyze the scenario where there are any number of pools suffering selfholding attack in both Ethereum and Bitcoin. The model in this paper can capture the behaviors of a more realistic and more general scenario, compared with the existing models. Moreover, our model and formulas can also be applied to evaluate a blockchain system, which uses a similar reward mechanism and is vulnerable to selfholding attack. Our work can help design a more secure blockchain incentive mechanism and an in-pool reward mechanism.

Selfish mining, as a serious threat to blockchain, has been attracting attentions from academic and industry. Stochastic modeling has been explored to quantitatively investigate selfish mining in imperfect blockchain networks. However, prior modeling-based analysis approaches have some of the following issues: (1) only focus on Bitcoin or Ethereum, or (2) ignore extended forks and just consider natural forks, or (3) only compute the mining revenue without assessing the performance and security of the blockchain system when the system suffers from selfish mining. In this paper, we aim to address these issues. We build a Markov chain to make quantitative analysis of selfish mining in imperfect Bitcoin and Ethereum networks with natural and extended forks. Formulas are derived to calculate the mining revenue for the selfish pool (comprising selfish miners) and honest miners, respectively. Moreover, we derive the formulas of performance metrics (namely, transactions per second and stale block ratio) and the formula of security metric (namely, the probability of double-spending success) of the system. These quantitative results can help understand the impact of selfish mining on imperfect blockchain networks and then help the detection of selfish mining.

The fantastic growth in cybersecurity attack frequency and sophistication over the years advances the development of Moving Target Defense (MTD) technology. Migration-based dynamic platform technique (DPT), one of MTD techniques, is expected to significantly improve cyberspace security by migrating service across multiple platforms according to the predefined policy. However, the existing random migration policies cause unnecessary cost when the service platform is not under attack, which indicates the necessity of combining DPT with traditional detection-based defense mechanism to make migration decision. In this paper, we propose a Continuous-Time Markov Decision Process (CTMDP)-based dynamic platform defense model against multi-stage attacks, which can determine the optimal service migration timing based on the system reward. To maximize the expected total discounted reward of the system, we utilize the value iteration algorithm to determine the optimal policy which defines what action to be taken in a specific state. Experiments are carried out to demonstrate that our CTMDP-based dynamic platform defense model obtains higher expected total discounted reward than using random migration policies. We also investigate the effects of platform numbers and discount factors on the system reward.

This work proposes Practical Byzantine Fault Tolerance (PBFT) ordering service needed for block formation in permissioned blockchain environments. Contrary to current PBFT implementations that only provide a single point of entry to the ordering service, we allow each ordering node to act as an entry point that proposes and conducts the consensus process of including new record in the distributed ledger. To ensure atomicity of record insertion in distributed ledger, we have developed a bandwidth reservation protocol that uses a modification of CSMA/CA protocol to regulate access to the broadcast medium formed by the P2P network of TCP connections between orderers. We have modeled record insertion service time in a cluster where ordering nodes have random position within Cartesian coordinate system. We have also modeled total request access time to the ledger which includes waiting time in the orderer's queue and record insertion time. These models are used to evaluate system performance under variable request rate ordering service, variable number of nodes and variable physical cluster dimensions. Our results show the interaction between decreased request waiting time in orderer's queue and increased contention among orderers when the number of orderers increases for the given total request arrival rate. This interaction is also investigated for two different physical cluster sizes which affect record insertion time. The interplay of request rate, number of orderers and physical cluster size determines system capacity expressed in total request rate. Our model can be used to make the trade-off between the required system capacity, number of orderers, and physical cluster dimensions under constraints on Byzantine fault rate.

Selfish mining strategy allows miners to gain unfair advantage and excess revenue in Bitcoin network, but it also disrupts the normal operation of the network. In this work, we analyze the impact of selfish behavior on the Bitcoin network through a number of performance indicators such as network connectivity, block arrival rate, node response time, and block delivery time for selfish and honest blocks, respectively. We also discuss the probability of unintentional as well as intentional forks. We have found that the impact of selfish mining on network performance is noticeable, and in extreme cases, disproportional to the number of selfish miners or their hash power compared to honest nodes. Our analysis has also found that forking probability is dominated by intentional forking resulting from selfish behavior, which has the potential to increase the ledger inconsistency time and open the door to security attacks.

With the growing demand of data processing/storage from Internet of Things (IoT) users and the increasing maturity of Cloud-Edge technologies, it becomes more and more critical to develop an effective and efficient performance evaluation approach in order to enhance the performance of Cloud-Edge services. Analytic modeling is an effective evaluation approach. The existing modeling researches on edge and/or cloud computing either ignored workload heterogeneity or ignored delay constraint of IoT tasks. This paper develops a hierarchical model for capturing the behaviors of Cloud-Edge datacenters, which provides service to tasks with different service priorities and requesting different number of service resources. Formulas for calculating performance measures of interest are also developed. The approximate accuracy of the proposed analytic model is verified through comparing numerical results and discrete-event simulation results.

The aim of this work is to evaluate the impact of node churn –nodes leaving and rejoining the network– on the Bitcoin network. We provide a comprehensive analytical model for the churning process. We use a Continuous Time Markov Chain (CTMC) to describe the behavior of a node, and then apply the results to model the changes in connectivity and the impact on network performance. We analyze the time needed to resynchronize a node upon rejoining the network and find that sleep times of the order of hours require synchronization times limited by a minute. We estimate the impact of sleep and synchronization time on overall network connectivity and block/transaction distribution time. Our results show that networks with less than 4000 nodes are sensitive to churn. This occurs due to opposing impact of decrease in network size (and diameter) due to sleep time and increase of communication load per node. However, the impact of churn on network with more than 4000 nodes is noticeable but small enough to make a large Bitcoin network fairly resilient to churn.

Dynamic participation of nodes, also known as churn, is quite common in P2P networks, and Bitcoin network is no exception. The impact of churn becomes more pronounced when nodes with different roles and functionality exist. In this paper we analyze node churn in Bitcoin network where ordinary nodes generate transaction traffic and distribute and verify blocks, while relay nodes that just distribute blocks, but have a larger number of connections. We use the tools of probabilistic analysis and Markov chains, and show that churn of relay nodes has a higher impact on traffic performance than that of ordinary nodes. We introduce two different Continuous Time Markov chains (CTMC) for ordinary and relay nodes to model each type of node’s behavior separately. Our results indicate that node sleep impacts the performance more in networks where the proportion of relay nodes is lower, and also that block and transaction delivery times are higher in those cases. Also, we find that the time needed for a node to synchronize upon rejoining the network after sleep is dominated by the time required for block and transaction verification.

Ultra-dense networks (UDN) are considered as one of the key technologies for advancing the widespread deployment of 5G networks. To provide continuous and reliable connectivity to user devices and to achieve the integrity and authenticity of communication, UDN needs to address the challenges related to authentication and authorization of information. Existing authentication and key agreement (AKA) schemes are not appropriate for the ultra-dense deployment of access points due to excessive authentication and/or computation overhead. This paper proposes a novel lightweight batch authentication and key agreement (LBAKA) scheme for user-centric UDN scenarios by adopting lightweight batch authentication solution and one-to-one key agreement, and by using mutual authentication to verify the credibility of both sides of the communication. The proposed LBAKA can maintain privacy of identity information under replay, impersonation and man-in-the-middle attacks in user-centric UDNs. In terms of computation and communication overhead, our simulation results show that LBAKA outperforms other similar schemes in user-centric UDNs.

Vehicular cloud computing (VCC) is composed of multiple distributed vehicular clouds (VCs), which are formed on-the-fly by dynamically integrating underutilized vehicular resources including computing power, storage, and so on. Existing proposals for identity-as-a-service (IDaaS) are not suitable for use in VCC due to limited computing resources and storage capacity of onboard vehicle devices. In this paper, we first propose an improved ciphertext-policy attribute-based encryption (CP-ABE) scheme. Utilizing the improved CP-ABE scheme and the permissioned blockchain technology, we propose a lightweight and privacy-preserving IDaaS architecture for VCC named IDaaSoVCC. It realizes lightweight and privacy-preserving access control of vehicles’ personally identifiable information (PII) in a large distributed vehicular cloud system. Security analysis demonstrates the security features of IDaaSoVCC, most notably forward secrecy, confidentiality and identity information privacy. Meanwhile, we verify that IDaaSoVCC is feasible and practical in a large distributed VC system through extensive simulations.

The widespread application of the Hyperledger Fabric platform and the timeliness requirement of transactions on the platform necessitate the effective performance evaluation of transaction processing. The existing evaluation researches on Hyperledger Fabric ignored transaction endorsement failure (due to transaction endorsing duration timeout) and/or ignored block timeout. This paper considers these two timeout constraints and develops a hierarchical model for Hyperledger Fabric v1.4 transaction process from the time when transactions are submitted by clients until the completion of validating/committing transactions as a block. Formulas for calculating performance measures, including platform throughput, transaction rejection probability and mean transaction response delay, are derived. Extensive numerical analysis and simulations are carried out to verify the approximate accuracy of the model and formulas. Moreover, numerical analysis is applied to illustrate the impact of various parameters on performance measures.

TGax aims at developing the IEEE 802.11ax protocol to provide enhanced throughput and power efficiency in dense WiFi deployment environments. The new specification shifts the focus from EDCA access to point coordination access, which aims at improving network utilization and power efficiency. Furthermore, it introduces, for the first time, the concept of RU allocation and orthogonal frequency division multiple access (OFDMA) techniques. The new specification addresses the spectral inefficiency in existing transmission by including schedule-based multi-user multiple-input, multiple- output (MU-MIMO) and multi-user OFDMA (MU-OFDMA) techniques to facilitate multi-user uplink transmission for high efficiency (HE) devices. However, complete adoption of the HE protocol is likely to take place over a period of time to offset the deployment cost. To ensure the coexistence of non-HE devices during the transition period, EDCA based single user transmission will remain the basic access technique and a focal point of spectral inefficiency for non-HE devices in the uplink direction. Motivated by our work on the performance of IEE 802.11ac, we propose an EDCA based uplink transmission technique for non-HE devices that allows multi-user transmission to improve spectral efficiency in coexistent WLAN networks.

As modern vehicles and distributed fog services advance apace, vehicular fog services (VFSs) are being expected to span across multiple geo-distributed datacenters, which inevitably leads to cross-datacenter authentication. Traditional cross-datacenter authentication models are not suitable for the scenario of high-speed moving vehicles accessing VFS, because these models either ignored user privacy or ignored the delay requirement of driving vehicles. This paper proposes a blockchain-assisted lightweight anonymous authentication (BLA) mechanism for distributed VFS, which is provisioned to driving vehicles. BLA can achieve the following advantages: 1) realizing a flexible cross-datacenter authentication, in which a vehicle can decide whether to be reauthenticated or not when it enters a new vehicular fog datacenter; 2) achieving anonymity, and granting vehicle users the responsibility of preserving their privacy; 3) it is lightweight by achieving noninteractivity between vehicles and service managers (SMs), and eliminating the communication between SMs in the authentication process, which significantly reduces the communication delay; and 4) resisting the attack that the database governed by one center is tampered with. BLA achieves these advantages by effectively combining modern cryptographical technology and blockchain technology. These security features are demonstrated by carrying out security analysis. Meanwhile, extensive simulations are conducted to validate the efficiency and practicality of BLA.

This paper presents a constrained application protocol enabled multithreaded Internet of Things (IoT) gateway that allows reliable and quick access to big data from IoT domains. We consider a proxy caching policy to accelerate the content delivery rate of sensor data while reducing the energy consumption of corresponding nodes. We propose a selective caching policy in which resource validation requests are sent based on user requests, besides updates from IoT nodes. We also describe an analytical model to evaluate the performance of multithreaded IoT gateway under various traffic conditions to meet the quality of service constraints. The proposed model is evaluated over single hop IPv6 over low-power wireless personal area networks/IEEE 802.15.4 cluster. The performance evaluation clearly shows the effectiveness of our model in providing fast response and reduced energy consumption of the resources.

Open vSwitch (OVS) is a popular virtual switch implementing OpenFlow, which often works in Linux system. The development of Cloud and Edge datacenters accelerates its popularity, especially with the emergence of 5G mobile networks. Performance analysis of a network system with OVS could help uncovering of performance bottlenecks and improving system performance. Analytic modeling is an effective performance evaluation approach. Existing analytical models of OVS ignored the characteristics of the system where OVS works. Thus, it is hard, if not impossible, to detect performance bottlenecks. This paper proposes a novel analytical model to evaluate the performance of Linux network system with OVS. Different from exiting models, our model can capture key steps, each of which consumes CPU in the packet forwarding process. Our model also enables the computation of a set of performance measures, including packer sojourn time and blocking probability. The approximate accuracy of the proposed model is validated by comparing numerical results with simulation results under various system parameter settings.

Mobile devices may offload their applications to a virtual machine running on a cloud host. This application may fork new tasks which require virtual machines of their own on the same physical machine. Achieving satisfactory performance level in such a scenario requires flexible resource allocation mechanisms in the cloud data center. In this paper we present two such mechanisms which use prioritization: one in which forked tasks are given full priority over newly arrived tasks, and another in which a threshold is established to control the priority so that full priority is given to the forked tasks if their number exceeds a predefined threshold. We analyze the performance of both mechanisms using a Markovian multiserver queueing system with two priority levels to model the resource allocation process, and a multi-dimensional Markov system based on a Birth-Death queueing system with finite population, to model virtual machine provisioning. Our performance results indicate that the threshold-based priority scheme not only performs better, but can also be tuned to achieve the desired performance level.

In this paper, we consider Internet of Things (IoT) domain running multicasting constrained application protocol (CoAP) over IEEE 802.15.4 network ended by CoAP proxy/cache. We examine the features of CoAP multicasting in order to ensure freshness of data in the cache as a function of the leisure parameter which allows devices to reply in arbitrary (random) time periods after receiving multicast GET request. We also investigate communication delay in the IoT domain and daily energy consumption of devices under several leisure schemes which may be implemented at the application level or at the medium access control layer. The impact of the leisure parameter appears to be critical for congestion avoidance. We show that a combination of proactive and reactive cache update with appropriate multicast leisure scheme can achieve low probability of outdated data while limiting the energy expenditure of nodes to a satisfactory value. Furthermore, best performance with respect to delay is obtained when the leisure period is integrated in the CSMA/CA backoff process.

The constrained application protocol (CoAP) observe feature has the potential to achieve fast communication and low energy consumption. We have analyzed a CoAP proxy which stores observed data from multiple Internet of Things (IoT) nodes that belong to single IoT domain. To maintain the freshness of cached records under random data arrivals, we have implemented the evaluation of Max-Age parameter at the proxy. We have also implemented congestion control at both IoT nodes and proxy, and show that it interacts with data freshness estimation at the proxy. Our results demonstrate the capacity limits of a single IoT domain against cluster size, interobservation time, proxy re-registration rate, ratio of confirmable/nonconfirmable observations, and presence of congestion control.

The formation of cognitive personal area networks (CPANs) requires a number of nodes to connect to a dedicated coordinator node. In this paper, we propose a probabilistic blind rendezvous protocol that allows nodes to concurrently rendezvous with the CPAN coordinator. This protocol allows nodes to arrive independently and their rendezvous times to overlap partially or fully with one another. We then develop a probabilistic model of the rendezvous process for both a single node and a group of nodes. The model shows that the rendezvous time, in both cases, exhibits hyperexponential behavior with large coefficient of skewness and, consequently, large variability, which may be approximated with a Gamma distribution. Furthermore, the mean group joining time tends to flatten and may even converge to a finite limit when the number of nodes is sufficiently high. However, the variability remains high due to a long tail of the distribution.

In this paper, we examine the impact of power ramping, number of retransmission attempts, and limitations of the physical downlink control channel (PDCCH) on the performance of random access in Long Term Evolution/Long Term Evolution-Advanced networks. We demonstrate that positive feedback exists between the maximum number of retransmissions, age-based power ramping, and PDCCH deficiency. As the result, system capacity is decreased and performance deteriorates abruptly under moderate to high traffic intensity. We show that, under power ramping and default PDCCH capacity, increasing the number of retransmissions beyond 1 or at most 2 does not bring any benefits and, in fact, is detrimental to system capacity. Increasing PDCCH capacity would enable the benefits of power ramping and allow more retransmission attempts. However, increasing the number of retransmissions combined with power ramping, while helpful under moderate to high load, will decrease system capacity.

Vehicle-to-everything (V2X) has been regarded as an important enabling technology for future intelligent transportation systems (ITS). Safety-critical applications in V2X require authentication of nodes and messages, and also need to preserve the privacy of vehicles. Pseudonymity plays an important role in V2X communication by satisfying both security and privacy requirements. In this paper, we analyze the weaknesses of a recent relevant work named Issue First Activate Later (IFAL), which is the leading European candidate for V2X. We then propose a novel lightweight, secure and privacy-preserving pseudonym changing scheme. Through the security analysis, we show that the proposed scheme achieves the asynchronous key agreement, and realizes both robust forward secrecy and backward secrecy while keeping security functionalities of IFAL. Furthermore, the performance analysis is conducted on Arduino Mega 2560 to illustrate that the proposed scheme is feasible and practical. © 2014 xxxxxxxx. Hosting by Elsevier B.V. All rights reserved.

The 802.11ac version of the popular IEEE 802.11 protocol aims to boost performance by increasing the channel bandwidth and allowing downlink multiuser multiple-input multiple-output (MIMO)—i.e., simultaneous transmission to multiple clients in the downlink direction. In this paper, we evaluate the performance improvements of multiuser Transmission Opportunity (MU-TXOP) sharing in this scenario under nonsaturated load and non-ideal channel condition, using a novel analytical model based on discrete Markov chain and E-limited M/G/1 queuing model. Our results show that MU-TXOP sharing achieves up to 105% gain in throughput compared to the case without MU-TXOP sharing. Moreover, the low-priority traffic benefits most from MU-TXOP sharing, with up to 150% throughput gain at low traffic intensity due to availability of additional transmission opportunities for secondary ACs.

Long Term Evolution (LTE) and its revision, Long Term Evolution-Advanced (LTE-A), were designed for high performance communications between devices operated by human users. However, when these networks are used for Machineto- Machine (M2M) traffic, i.e., communications between smart electronic devices that do not need human supervision, performance is far from satisfactory. This is mostly due to the overload condition created when a large number of M2M devices attempts random access using the fourstep handshake prescribed by the LTE standard. In this article, we describe an overlay network that allows M2M devices to access the network without going through the full handshake. We show that the overlay provides much improved performance for M2M traffic, especially when the transmission power of M2M devices is slightly increased to combat the overload condition, and is capable of supporting M2M traffic in device-todevice (D2D) communication mode.

Radio-frequency (RF) recharging can extend maintenance-free operation of wireless sensor networks. However, the period between recharging is limited by the distance between the most distant sensor node and the master, which sends out recharging pulses. To increase this period, we propose a zoning scheme in which nodes are logically grouped into circular zones centered at the master so that nodes in a given zone send their data to their neighbors in the next closer zone, which act as relays. We describe and analyze a polling Medium Access Control (MAC) protocol that supports zoning and relaying through a probabilistic model of the energy depletion process and a queueing model of the packet transmission process. Our results indicate that zoning extends the time interval between recharge pulses and leads to equalization of node lifetimes, but limits the available data transmission bandwidth as well.

Bridging between two cognitive personal area networks (CPANs) is a fundamental step toward a reliable and efficient routing protocol. In this paper, we describe a bridging protocol for two-hop cognitive networks that use the transmission tax-based medium access control and propose ways to prioritize bridge traffic over that of ordinary nodes in both CPANs. We develop an analytical model based on probabilistic modeling and queueing theory to evaluate the performance of the bridging protocol. We validate the network performance by analyzing the waiting time of local and nonlocal packets and how the node or bridge transmission is affected by the collision with primary-source activity. Our results provide insights into the impact of various traffic and network parameters on the performance of two-hop bridging. The results indicate that the proposed protocol is effective and efficient when the bridge transfers a moderate amount of traffic.

Long-Term Evolution (LTE) and its improvement, Long-Term Evolution-Advanced (LTE-A), are attractive choices for Machine-to-Machine (M2M) communication due to their ubiquitous coverage and high bandwidth. However, the focus of LTE design was high performance connection-based communications between human-operated devices (also known as human-to-human, or H2H traffic), which was initially established over the Physical Random Access Channel (PRACH). On the other hand, M2M traffic is mostly based on contention-based transmission of short messages and does not need connection establishment. As a result, M2M traffic transmitted over LTE PRACH has to use the inefficient four-way handshake and compete for resources with H2H traffic. When a large number of M2M devices attempts to access the PRACH, an outage condition may occur, furthermore, traffic prioritization is regulated only through age-based power ramping, which drives the network even faster towards the outage condition. In this article, we describe an overlay network that allows a massive number of M2M devices to coexist with H2H traffic and access the network without going through the full LTE handshake. The overlay network is patterned after IEEE 802.15.6 to support multiple priority classes of M2M traffic. We analyse the performance of the joint M2M and H2H system and investigate the trade-offs needed to keep satisfactory performance and reliability for M2M traffic in the presence of H2H traffic of known intensity. Our results confirm the validity of this approach for applications in crowd sensing, monitoring and others utilized in smart city development.

In this work we discuss architectural alternatives for the design of a proxy that interconnects IoT domains running CoAP with the rest of the Internet including micro datacenters and other domains building scalable hierarchical architectures. We assume that the CoAP domain is terminated by an IoT proxy with cache, and we investigate several design alternatives, assuming that the proxy autonomously maintains data freshness. Our analysis indicates that multicast and observe-based proxies perform better than the default POST/GET approach in terms of successful data transmission, round trip delay and energy consumption, with the multicast option having a slight advantage.

Recharging through radio frequency (RF) pulses is a promising approach to enhance the lifetime of wireless sensor networks (WSNs). In this paper, we propose a polling-based MAC protocol with round robin scheduling under E-limited service policy. In this model, the WSN coordinator sends a recharging pulse upon reception of a recharging request from one of the nodes. As both recharging and data communication use the same RF band, the latter process is interrupted by the former. A probabilistic model for energy depletion within the proposed MAC along with queueing delay model is evaluated as well. Later, we assess the behavior of time interval between two consecutive recharging events and packet waiting time under varying network size and traffic load.

Spectrum decision-that is, the selection of a channel for the next hop-is one of the most important factors that affect the performance of a channel-hopping cognitive network. In this paper, we compare the performance of a number of channel selection algorithms through the probability of collisions with primary user transmissions. The results indicate that a simple histogram-based selection algorithm performs the best, except in the somewhat unrealistic scenario where primary users are homogeneous with respect to mean period and mean duty cycle of their channel activity, in which case selecting the next-hop channel among those that have most recently turned idle offers the best performance. Furthermore, histogram-based selection is shown to be quite resilient to errors inherent to channel sensing and is thus a primary candidate for a wide range of applications of channel-hopping cognitive networks. Copyright © 2014 John Wiley & Sons, Ltd.

We investigate the performance of a recovery mechanism in channel-hopping cognitive networks. The recovery algorithm is based on a list of backup channels to be used as alternatives if primary-user activity interrupts ongoing communication on the current channel; if all backup channels are exhausted without success, the nodes revert to a blind-rendezvous mechanism. We evaluate the performance of the recovery algorithm using the tools of probabilistic analysis and renewal theory and validate the results through simulation. We discuss the impact of various network and channel parameters on the performance of the recovery algorithm and show the importance of accurate sensing information for successful recovery.

In a vehicular ad hoc network VANET, a road-side infrastructure or road-side unit RSU is anticipated to be installed at some road-side location. This exposes the VANET to several different adversaries. In this paper, we present an authentication scheme for infrastructure-generated safety messages using an identity ID-based proxy signature and verification mechanism. An ID-based technique offers a certificate-less public key verification, while a proxy signature provides flexibility in message authentication and trust management. We incorporate an ID-based proxy signature framework with the standard elliptic curve digital signature algorithm for safety application messages from RSU. We also provide forwarding of safety message components ensuring the accountable authentication of RSU's application messages. Security analysis and network simulation prove that our scheme is resilient to all major security threats, compatible to standards and efficient in terms of computation complexity. We also conduct simulation experiments to determine the most suitable access classes for on-board unit and RSU.

Advanced metering infrastructure AMI is one of the key elements in smart grid, which facilitates the communication of metering data to a substation in one direction and control messages in the reverse direction. Using wireless technologies and communication devices e.g., smart meters, which are located in the physically insecure places, makes the AMI vulnerable to cyber attacks. In order to ensure the reliability and security of AMI, attack prevention techniques and intrusion detection systems IDSs should be in place to protect the AMI communications from malicious attacks and security breaches, respectively. In this paper, we discuss the security requirements and vulnerabilities of AMI and review the existing threat prevention and detection solutions. We propose an IDS for neighborhood area network NAN in AMI, taking into account the NAN-specific requirements. Copyright © 2012 John Wiley & Sons, Ltd.

In this paper, we investigate the capacity limits in a variable duty cycle VANET that uses the IEEE 802.11p standard. We show that the default value of duty cycle that allocates time equally between control and service channels leads to unbalanced performance and that the performance of typical traffic on those channels can be greatly improved by judicious choice of the value for duty cycle. We find the values of spatial density of vehicular traffic that lead to spatial saturation of network traffic. In addition, to model the distribution of the vehicles on the road segment, we used Poisson distribution, as well as Erlang-k distribution. Copyright © 2012 John Wiley & Sons, Ltd.

We investigate the performance of simple cognitive personal area networks (CPANs) with cooperative sensing. Nodes are equipped with small buffers of capacity K each, and each node is allowed to transmit a batch of up to μ packets in one transmission cycle. Upon transmission, each node must support the operation of the CPAN by performing sensing duty in the amount obtained by multiplying the number of packets sent in a batch by a variable penalty coefficient. We model this system and show the relationship between values of design parameters and piconet performance. We also show that performance and bandwidth utilization can be improved by a simple technique of dynamically adjusting the duration of the superframe to cater to instantaneous traffic volume. Copyright © 2011 John Wiley & Sons, Ltd.

In this paper, we investigate the performance of networks built from single-channel devices that use wireless access in vehicular environment protocols. We consider several traffic combinations, each of which presents a mix of traffic classes, over control and service channels. Our results show that time switching between the channels causes synchronization of backoff processes, which increases the frame collision probability, in particular for small sizes of contention windows. We also evaluate the impact of the interruption of the backoff process by inactive channel time, which gives rise to a probability distribution with repeated tails and a coefficient of variation larger than 1. Our model can also be used to evaluate different sets of enhanced distributed channel access parameters and to select the channel duty cycle according to the policy of the network operator.

Cognitive radio technology necessitates accurate and timely sensing of primary users' activity on the chosen set of channels. The simplest selection procedure is a simple random choice of channels to be sensed, but the impact of sensing errors with respect to primary user activity or inactivity differs considerably. In order to improve sensing accuracy and increase the likelihood of finding channels which are free from primary user activity, the selection procedure is modified by assigning different sensing probabilities to active and inactive channels. The paper presents a probabilistic analysis of this policy and investigates the range of values in which the modulation of sensing probability is capable of maintaining an accurate view of the status of the working channel set. We also present a modification of the probability modulation algorithm that adapts the weighting factor to changes in perceived duty cycle of primary users' activity, and show that it achieves minimum sensing error in a wide range of the values of that duty cycle.

In this paper, we propose and evaluate a cognitive personal area network (CPAN) suitable for wireless monitoring and control outside the Industrial, Scientific and Medical (ISM) band. Network is based on frequency hopping but the channels are selected on the basis of spectrum sensing performed by the nodes. Nodes balance their data collecting activity and spectrum sensing such that the duration of spectrum sensing done by a node is proportional to the number of packets previously transmitted by that node. We show that the operation of a node in this setup can be modeled as a gated exhaustive round-robin system with vacations, and analyze the performance of the system. The impact of the value of the penalty factor, which determines the duration of sensing activity with respect to transmission, on packet access delay and stability limits of the system is discussed in detail. Copyright © 2009 John Wiley & Sons, Ltd.

Cognitive radio technology necessitates accurate and timely sensing of the primary users' activity on the chosen set of channels. If sensing error is unacceptably high, we can reduce the number of working channels so as to improve the channels-vs.-sensing nodes ratio, and undertake differential or split sensing in which subsets of sensing nodes target idle and active channels, respectively. The paper presents a probabilistic analysis of the sensing process, including the split sensing policy, and investigates the range of values in which such, incomplete sensing is capable of maintaining an accurate view of the status of the working channel set.

In this paper we consider the interconnection of an IEEE 802.15.4 body area network (BAN) in which nodes sense physiological variables such as electrocardiography (EKG), electroencephalography (EEG), pulse oximeter data, blood pressure and cardiac output, with an IEEE 802.11b room/ward WLAN. We model the operation of this two-tier network assuming that 802.15.4 BAN operates in CSMA-CA mode and that the BAN coordinator acts as the bridge which conveys BAN packets to the 802.11b access point. We analyze the two-hop network delay and discuss the mutual interaction of different data streams as well as impact of the number of bridges on packet delay.

Cognitive radio technology necessitates accurate and timely sensing of primary users' activity on the chosen set of channels. The simplest selection procedure is a simple random choice of channels to be sensed, but the impact of sensing errors with respect to primary user activity or inactivity differs considerably. In order to improve sensing accuracy and increase the likelihood of finding channels which are free from primary user activity, the selection procedure is modified by assigning different sensing probabilities to active and inactive channels. The paper presents a probabilistic analysis of this policy and investigates the range of values in which the modulation of sensing probability is capable of maintaining an accurate view of the status of the working channel set. We also present a modification of the probability modulation algorithm that allows for even greater reduction of sensing error in a limited range of the duty cycle of primary users' activity. Finally, we give some guidelines as to the optimum application ranges for the original and modified algorithm, respectively.

Efficient operation of cognitive personal area networks (CPANs) necessitates accurate and efficient sensing of the primary user activity. This is accomplished in a cooperative manner by a number of nodes in the CPAN; the results of sensing are combined by the CPAN coordinator to form a comprehensive and timely channel map. The error of the sensing process is affected by various factors, including the ratio of the number of sensing nodes to the number of channels. In this paper, we present a probabilistic model of the sensing process and derive an analytical solution for the minimum number of sensing nodes that keeps the sensing error below prescribed limits. Then, we discuss three differential sensing policies in which separate sets of sensing nodes target idle and active channels only and show that the policy in which idle channels are given priority, but not exclusive treatment, achieves the best performance, as measured by the number of channels for which the information in the channel map is erroneous and the mean duration of that erroneous information.