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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.

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.

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.

Compact block protocol aims to reduce bandwidth usage and, possibly, latency in the Bitcoin network. In this work, we present an analytical model to evaluate the impact of churning nodes on the Bitcoin network when the compact block protocol is used. We use a Continuous Time Markov Chain to model wake-up and sleeping behavior of each node in the network. We also calculate synchronization time, including transaction deficit recovery, when a node rejoins the network. When a node is absent from the network, it misses blocks mined during its absence but also some of the transactions which may be omitted from the subsequent compact blocks. Our results indicate that synchronization time takes more than a minute when node is away from the network for several hours. Moreover, the majority of synchronization time is spent on block verification and transaction deficit recovery.

Practical Byzantine Fault Tolerance (PBFT) consensus algorithm is unsuitable for Internet of things (IoT) applications due to the need for a single view leader. In this work we propose to augment PBFT with a contention-based bandwidth reservation phase that allows any ordering node to initiate a new consensus round. We model the operation of the proposed algorithm, and show that system throughput is not significantly affected by the increased communication load when the number of ordering nodes increases, as the load per ordering node actually decreases. In this fashion, the proposed algorithm allows the deployment of wide area IoT networks that use PBFT-based consensus.

This work proposes and evaluates a Practical Byzantine Fault Tolerance (PBFT)-inspired ordering service for IoT data collection and block formation in a permissioned blockchain environment. We implement an algorithm for atomic insertion of request to ordering service in which each ordering node can initiate insertion and lead the consensus protocol, unlike traditional current implementations of ordering service which rely on a single point of entry. We have modeled record insertion service into the P2P ordering service with constant number of nodes, variable request rate, and known distribution of one-way propagation delays among the ordering peers. Performance results show the behavior of system descriptors and the limits of system capacity expressed in terms of total request rate.

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.

The IEEE 802.11ac amendment enhances WLAN throughput by exploiting the spatial diversity of the antennas in a multi-user multi-input multi-output downlink transmission. Still, network resources remain under-utilized in uplink transmission due to single-user communication. In this paper, we propose an access point-controlled MAC protocol (A-MAC) that enables simultaneous transmissions from multiple STAs in uplink. The protocol uses the EDCA channel access technique to initiate multi-user transmission and the OFDMA method to transmit multiple RTSs simultaneously. It also introduces the explicit channel sounding technique by using dedicated OFDM subcarrier blocks for each user. Performance measurement shows that network throughput of the A-MAC is 150% higher than that of a single uplink transmission, thanks to the availability of concurrent multiple RTS transmissions in the uplink. The proposed protocol shortens the backoff time by up to 50% for all traffic categories due to concurrent multiple transmissions and thus enhances the battery life of the nodes. We observe that although the smaller backoff window of high-priority traffic category enhances the network throughput, higher intensity of high-priority traffic drives the network faster to saturation. Furthermore, better network stability and fairness among different traffic categories can be achieved when the dominant traffic has low priority.

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 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.

Multi-Access Edge Computing (MEC), making computing resources extend to the edge continuously, plays a key role in 5G (Fifth Generation) networks. User Plane Function (UPF), as an important network function, can steer the traffic to the MEC applications and 5G core network in the integration of MEC and 5G architecture. Edge UPF (EUPF) runs in a virtual machine (VM) hosted by a virtual machine monitor (VMM) at the edge of the network. However, EUPF is likely to suffer more frequent network attacks than in the core network. The vulnerability of the virtualized environment itself also expands the attack surface for adversaries. Security protection of EUPF is urgently needed. Rejuvenation techniques play a key role in defense and service recovery. The existing researches focused on the deployment of EUPF and ignored the dependability analysis of EUPF service.

In this work we analyze the blockchain forking events, blockchain partitioning, and duration of inconsistent state of the ledger in a Bitcoin delivery network. Using a comprehensive probabilistic model, we obtain the probability distribution of two- and three-way forks, the forked partition sizes, and the duration of ledger inconsistency until the resolution. We show that the three-way forking probability is substantially lower than that of a two-way forking and that the partition sizes in the case of two-way forking tend to equalize when the number of nodes increases. Finally, we show that the duration of ledger inconsistency state exhibits long tail probability distribution which means that successive forking events can force the ledger to remain inconsistent for long time.

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.

We have developed an analytical model for a non-saturated IEEE 802.15.6 wireless body area network (WBAN) operating under an error-prone channel. The most suitable vehicle for improving network performance was found to be the choice of access phase lengths based on traffic loads for different user priorities (UPs). It was also found that the deployment of exclusive access phase (EAP) is not necessary in a typical WBAN; in fact, short exclusive and random access phases (EAP and RAP, respectively) lead to inefficient use of available bandwidth. We have also found that four user priorities (out of the eight available) typically suffice to achieve even the most stringent requirements for WBAN performance.

Bitcoin and Ethereum, the most famous blockchain-based cryptocurrencies, both use Proof-of-Work protocol to achieve consensus, which is vulnerable to selfish mining. The existing researches on selfish mining analysis focused on Bitcoin, or ignored the blockchain details, or only investigated mining revenue without considering system performance and security. This paper aims to quantitatively evaluate the influence of selfish mining in an imperfect blockchain network from the perspective of honest miners (system performance and security) and selfish miners (selfish mining revenue ratio). We develop a novel Markov model to capture the behaviors of honest and selfish miners in both Bitcoin and Ethereum. Our model can also capture natural forks (occurring due to block propagation delay) and the varying distance between uncle and nephew blocks in Ethereum. Formulas are derived to calculate mining revenue, system performance and security metrics. The proposed model and metric formulas are validated by (1) comparing our numerical with simulation results, and (2) comparing our numerical results with the existing work results. Numerical analysis is carried out to investigate selfish mining impact over diverse parameters. These quantitative results can help detect whether there are any selfish miners in the system, help design blockchain reward mechanisms and enhance security.

The Unmanned Aerial Vehicles (UAVs) play a significant role to alleviate the negative impacts of disasters by providing essential assistance to the rescue and evacuation operations in the affected areas. Then, the reliability of UAV connections and the accuracy of exchanged information are critical parameters. In this paper, we propose networking and security architecture for disaster surveillance UAV system. The networking scheme involves a two-tier cluster network based on IEEE 802.11ah, which can provide traffic isolation between the tiers. The security scheme guarantees the accuracy and availability of the collected information from the disaster area applying fingerprint features and data redundancy techniques, the proposed scheme also utilizes the lightweight Ring-Learning with Errors (Ring-LWE) crypto-system to assure the confidentiality of the transmitted data with low overhead.

In this paper we develop lightweight algorithms for monitoring and estimating data lifetime and round trip time at CoAP proxy. We deploy these algorithms in CoAP IoT domain with observe feature with random inter-observation times which can be a consequence of parameterized queries. Algorithms are based on kernel estimation of probability density distributions (pdf). As a result proxy maintains approximate pdfs of these parameters which can be used in congestion control and/or anomaly detection in IoT domain. Results show that estimations with 400-500 samples render satisfactory tradeoff between accuracy and computational complexity even under skewed probability distributions such as exponential distribution.

In this work we examine the tradeoffs involved in cache operation in an IoT domain controlled by a single Constrained Application Protocol (CoAP) proxy using IEEE 802.15.4 low power wireless personal area network technology. As the requirements for fresh data supplied to the clients and the reduction of traffic in the IoT domain are contradictory, a viable tradeoff is sought to obtain satisfactory performance. To this end, we compare the performance of a recently proposed group-based approach to that of a Bernoulli-scheduled, server-initiated proactive refresh, and show that the latter achieves superior cache hit ratio while offering substantial savings in terms of actual number of IoT domain messages exchanged.

IEEE 802.11ah protocol aims at providing network connectivity to a large number of end points while maintaining a satisfactory network performance. The RAW scheme of MAC access technique enables STAs to contend in different RAW slots and thereby reducing the chance of collision. In this paper we evaluate the performance metrics of the RAW scheme and observe that RAW scheme may be suitable for very small traffic condition. At higher traffic load, some of the nodes need to wait longer to transmit packets and network becomes unstable very quickly as the traffic for each node is increased beyond two packets per second in our test condition. The highest normalized network throughput achieved in this network is around 40%. Some important performance metrics like idle probability, backoff time and transmission probability are evaluated and studied in detail in this paper.

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.

We describe a priority-based CSMA/CA overlay network over LTE which is suitable for many application areas that require Machine-to-Machine (M2M) communications. The proposed overlay network uses LTE physical random access channel (PRACH) as the physical layer and a carrier sense multiple access with collision avoidance (CSMA/CA) mechanism similar to the one used in IEEE 802.15.6 Wireless Body Area Network (WBAN). We analyze the performance of H2H traffic in the presence of the overlay as well as the performance of the overlay itself, taking into consideration noise and sensing errors coming from the concurrent human to human (H2H) traffic in that same cell as well as in neighboring cells. We show that the overlay network allows fair coexistence of PM2M and H2H traffic, and that high priority M2M traffic is distinctly prioritized over low priority one, even though the latter still enjoys satisfactory performance.

In this paper we analyze the performance of a CoAP proxy with layered architecture and a built-in cache. The proxy acts as the gateway connected to the sensor nodes through an IEEE 802.15.4 low data rate wireless personal area network (LR WPAN). We investigate the impact of various traffic and proxy parameters on the performance of the proxy, in particular the interplay of the data validity interval defined through the CoAP Max-Age parameter.

The IEEE 802.11ax draft of high efficiency (HE) amendment to the ubiquitous 802.11 standard aims at increasing spectral and power efficiency of the network. However, the performance degradation due to hidden terminal problem had always been a concern especially in uplink transmission. Although the trigger based uplink transmission in IEEE 802.11ax is successful to some extent, the hidden node problem still persists in coexisting network. In particular, the uplink throughput is drastically reduced with the increase of packet arrival rate in presence of hidden node. To combat the hidden terminal problem, we propose to increase the carrier sensing threshold (CSTH) of STAs during association with HE access point (AP). Our analysis shows that this approach allows collision probability in uplink transmission to be reduced significantly.

The CoAP observe feature is a promising way to reduce energy consumption of IoT nodes and improve communication performance. To make the most benefit of this, the proxy which observes data from multiple nodes in a single IoT domain, must estimate the data lifetime and eliminate, or at least diminish, the impact of variability introduced by random transmission times from IoT nodes to proxy. We have investigated impact of lenient versus more conservative estimations of data freshness on traffic performance in the cluster and on energy consumption at IoT nodes. Results show that for exponentially distributed inter-observation times with mean of 60s, conservative estimations of Max\_Age run smoothly on clusters with well over 500 nodes.

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.

In this work we have examined aspects of reliable and scalable acquisition of big data from IoT domains. We have modeled the performance of CoAP enabled cross proxy IoT gateway towards the domain of CoAP enabled IoT devices. We focused on maintaining freshness of cache records at the proxy while maintaining low delay and low energy communications. We show that non-confirmable CoAP mode works well with acknowledged mode of 6LoWPAN/IEEE 802.15.4 cluster and that high delay and timeout values proposed in CoAP can be avoided. To support data freshness limit imposed by CoAP we have included sensor replicas which report the same variable. We have shown that addition of sensor replicas together with proactive cache update can ensure low record outdate probability while combination of proactive and reactive cache update can still have low outdate probability while limiting energy expenditure of nodes.

IEEE 802.11ac amendment enhances WLAN throughput by exploiting spatial diversity of antennas in MU-MIMO downlink transmission. However, in the existing framework ample network resources remain underutilized in uplink transmission due to single user communication. In this paper, we have proposed an efficient Access Point controlled MAC (A-MAC) protocol that enables concurrent multiple uplink transmissions for different priority traffic classes. Performance measurement shows that network throughput of A-MAC is 150\% higher than the throughput of single uplink transmission in existing IEEE 802.11ac protocol. We have achieve the highest payload throughput of 64\% when the number of nodes $N_{sum}=8$ and $\lambda=138$ packet/s at uniformly varying packet arrival rates for all STAs. As the number of nodes increases, the network throughput gradually decreases but the packet handling capacity of the network increases. The peak network capacity of 1200 packets/s is achieved with $N_{sum}=16$ and $\lambda=75$ packets/s for all STAs. Further increase of the number of nodes results in decreasing both network throughput and packet handling capacity of the network. We have also evaluated the performance metrics of our proposed A-MAC protocol under non-uniformly varying packet arrival rates for a fixed number of nodes $N_{sum}=24$. The analysis shows that when the network has higher intensity of low priority traffic, the aggregate packet handling capacity of the network is 1400 packets/s. However, as the intensity of high priority traffic increases, the aggregate packet handling capacity of the network decreases to 1000 packets/s. The results show that the more the higher priority packets arrive, the faster the network becomes unstable.

Sensor cloud is an extension of traditional sensor networks that virtualizes sensor nodes in order to achieve improved response time for client queries and reduction of energy consumption of physical sensor nodes in order to prolong their lifetime. In this paper we investigate information sharing in a sensor cloud with two types of sensors with different amount of data to send in each reading, and two types (classes) of client applications with different arrival rates. We show that caching of data readings can give noticeable improvements in performance, esp. at high arrival rate of client queries. Poll sharing amongst classes can also provide benefits but only in case where slower class polls are extended to update obsolete readings from the faster class (which may be done at no extra cost); other ways of sharing, including reading both values each time, are found to be inferior in terms of response time reduction. These findings can be operationalized to devise an efficient sensing policy for the sensor cloud.

Sensor cloud is an extension of traditional sensor networks that allows information sharing among users, improves response time to user requests, and reduces energy consumption of individual sensors to prolong their lifetime. In this paper we investigate the performance of data caching in a sensor cloud, assuming random selection of sensors to be read and a fixed duration of the time interval in which the sensor reading is valid. We show that significant improvements in performance, both with respect to response time and energy savings, can be achieved, depending on the percentage of sensors in each request, request arrival rate, and the number of concurrent servers issuing sensing requests.

In this paper, we have explored the possibility of using IEEE 802.11ac as the MAC layer solution for VANET to meet the new requirements for various types of broadband services for Vehicle to Infrastructure (V2I) wireless communication. We have proposed an efficient RSU controlled MAC protocol that enables uplink MU-MIMO transmission for different priority traffic categories. Performance metrics show that the throughput enhancement of proposed MAC in MU-MIMO uplink transmission is three times the throughput of a single user transmission. We observe that due to smaller contention window size, the mean backoff time for the highest priority messages remain in the range of millisecond even at high packet arrival rate and node density. The saturation throughput analysis clearly shows two desired operating points: highest network throughput and highest network capacity. We achieve a maximum payload throughput of 64\% at an aggregate packet arrival rate of 1100 packets/sec whereas 54\% network throughput is achieved at a maximum load of 1200 packets/sec. We observe that the stable operating load remains between 1100-1200 packets/sec in our model.

This paper presents inter-piconet communications in the scenario where a shared bridge node connects two Cognitive Personal Area Networks (CPANs). The bridge carries both inter-CPAN traffic and synchronization information. The bridge exchanges synchronization information in a prioritized manner, which ensures that the two CPANs can coexist without operating on the same channel at the same time. We validate the network performance by analyzing the frequency of synchronization information exchanges. The simulation results also provide insight into the impact of various traffic. The results indicate that the proposed method is effective and efficient when the traffic load and the frequency of synchronization information exchanges are low to moderate.

The formation of a Cognitive Personal Area Network (CPAN) involves a group of nodes connecting to a dedicated coordinator. In this paper, we propose a protocol for the formation of a CPAN in which nodes arrive randomly and their times to rendezvous (TTRs) with the CPAN coordinator may overlap, partially or fully, with one another. We develop an analytical model for the group joining time, i.e., the time to form the CPAN by an arbitrary number of nodes. Experimental results show that the time to form smaller size CPANs is mostly equivalent to the sum of all nodes' joining times. As the number of nodes gets larger, the group joining time flattens, which indicates that nodes that arrive later are more likely to join the CPAN before some of the nodes that arrived earlier.

IEEE 802.11ac standard provides an increase in performance by introducing the pioneering downlink multi-user MIMO technique which allows simultaneous transmission to multiple clients in the down-link direction [1]. In this paper we have evaluated MU-TXOP sharing probabilities in IEEE 802.11ac at different traffic intensities using analytical model based on discrete Markov chain and E-limited M/G/1 queuing model. Our results show that the low priority traffic group benefits most from MU-TXOP sharing and achieves 150% throughput gain at low traffic (12 Mbps).

In this paper we model and evaluate power ramping as a mechanism for achieving explicit access priority among traffic classes in LTE#x002F;LTE-A, taking into account preamble SINR considerations, preamble collisions, capture effect, and Physical Downlink Control Channel (PDCCH) deficiency. The results show that explicit power ramping can provide reasonable performance differentiation among traffic classes but it still cannot overcome coupling among traffic classes which exists due to preamble collisions and insufficient PDCCH resources.

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 scheme in which nodes are logically grouped into circular zones centered at the master, so that nodes in a given zone act as relays for their counterparts in the more distant zones. We describe and analyze a polling MAC protocol that supports zoning and relaying through a probabilistic model of the energy depletion process as well as a queueing model of packet transmission process. Our results indicate that zoning extends the time interval between recharge pulses and leads to equalization of node lifetimes.

Power ramping is one of the mechanisms proposed to help alleviate congestion during random access in LTE cells. We evaluate its performance taking into account preamble SINR considerations as well as Physical Downlink Control Channel (PDCCH) deficiency. Our results show that power ramping can speed up access at small to moderate loads, but that it is actually detrimental at moderate to high loads, with the ability to cause abrupt onset of saturation.

In this paper, we describe an VM2M overlay architecture where the overlay acts as the control channel (CCH) of VANET to transfer safety messages between vehicles and RSU. The VM2M overlay network is implemented over dedicated preamble codes in the physical layer and the medium access control (MAC) layer modeled as the IEEE 802.15.4 carrier sense multiple access (CSMA/CA) mechanism. In this paper, we implement priority based VM2M where higher priority is given to VM2M in the physical layer. To this end, VM2M preambles are transmitted with higher power than H2H. Due to large cell sizes and/or higher vehicle velocities in urban, sub-urban, and rural areas, and on highways, VM2M overlay is implemented using preamble format 2 with total duration of 2 ms. We compare the non-priority scenario, in which H2H and VM2M traffic access the base station simultaneously with the same power, to VM2M priority-based scenario where each preamble of M2M overlay is transmitted with higher power than any of non-overlay ones. The VM2M priority-based scenario is found to increase the capacity of VM2M subnetworks compared with non-priority scenario, without undue deterioration of the capacity left for H2H/SCH traffic.

Wireless sensor networks with radio frequency recharging of node batteries suffer from an imbalance in recharge amount on account of different distance to the master node. We describe an approach in which nodes are logically partitioned into a number of zones so that nodes in a closer zone act as relays for nodes in the next more distant zone. We show that the optimum partitioning can be found through exhaustive search, and propose a simple heuristic algorithm that can improve the performance without undue deterioration of the network bandwidth.