The Constrained Application Protocol (CoAP) is a lightweight communication protocol designed by the Internet Engineering Task Force (IETF) for wireless sensor networks and Internet-of-Things (IoT) devices. The reliability mechanism in CoAP is based on retransmissions after timeout expiration and on an exponential backoff procedure which is designed to be simple and adapted to constrained devices. In this research work, we propose a new exact analytical model to analyze the performance of CoAP in lossy wireless networks modeled by the well-known Gilbert-Elliott two-state Markov process. We also show how to compute several performance metrics using closed form expressions such as the observed loss ratio, goodput, and the delay before success with a time complexity no more than O(r) with r is the maximum re-transmission limit. This study provides insights about improving CoAP recovery mechanism and highlights the properties -- including the limitations -- of CoAP. Also, it presents guidelines to tune CoAP parameters dynamically in order to adapt to network losses caused by interference and mobility. The model is validated using the realistic environment Cooja/Contiki OS where theoretical and experimental results match very well.

International audience

The Constrained Application Protocol (CoAP) is a lightweight core protocol used for communication between devices in the Internet-of-Things. The CoAP standard defines a simple congestion control mechanism based mainly on retransmissions after timeouts and a binary exponential back-off procedure with randomization. However, the default parameters of this mechanism can affect negatively the efficiency of the protocol in severe network conditions. In this paper, we propose new exact mathematical models to study the performance of CoAP in lossy networks. This study provides useful insights in order to tune CoAP parameters and also highlights CoAP properties and limitations so that future better mechanisms can be designed adequately.

Named Data Networking (NDN) is an Information Centric Networks (ICN) solution that has recently attracted significant attention. NDN changes the Internet communication paradigm from the host-to-host IP model, to a name based communication model. In NDN, the requested Data can be retrieved from different sources and through multiple paths. This distinguished feature of NDN makes the traditional end-to-end congestion control schemes flagging with this new architecture. In this paper, we present a Hop-by-hop congestion control mechanism to regulate the Interest rate between the consumer and the congested router. Each NDN router continuously monitors its outgoing queues occupancy. When the queue size exceeds or falls below a specified threshold, an explicit notification is sent to downstream routers and consumers. The consumer and routers along the path then react by adjusting their Interest sending rates according to the available rate specified in the received notification. We prove the efficiency of the proposed solution and its ability to reduce the congestion impact and to maintain fairness per consumer. We highlight the advantages of our solution using different scenarios implemented in ndnSIM.

In order to cope with the exponential growth of mobile traffic, mobile operators need to access more spectrum resources. LTE in unlicensed spectrum (LTE-U) has been proposed to extend the usual operation of LTE in licensed spectrum to cover also unlicensed spectrum. However, this extension poses significant challenges especially regarding the coexistence between LTE-U and legacy systems like Wi-Fi. In case of LTE-U adopts Time-Division Multiplexing (TDM) schemes to share the spectrum with Wi-Fi, we expect performance degradations of Wi-Fi networks. In this paper, we quantify the impact of TDM schemes on Wi-Fi performance in a coexistence scenario. We provide detailed analytical models using two different random walk approaches to compute the probability of collision faced by Wi-Fi stations and their throughput performance. Besides, we derive the performance results using an exponential approximation which shows its insufficiency to capture the exact behavior. We implement the coexistence in the NS3 simulator and we show that the models estimate accurately the collision probability and the throughput experienced by Wi-Fi. The models are then used to study and compare different coexistence schemes showing for instance that the Wi-Fi frame size has a non-negligible impact on the performance of Wi-Fi users.

To address the mobile data growth challenges, mobile operators need to access more spectrum resources. LTE in unlicensed spectrum (LTE-U) has been proposed to extend the usual operation of LTE in licensed spectrum to cover also unlicensed spectrum, mainly at 5 GHz band due to its wide spectrum availability. However, this extension poses significant challenges especially regarding the coexistence between LTE-U and legacy systems like Wi-Fi. In case of LTE-U adopts Time-Division Multiplexing (TDM) schemes to share the spectrum with Wi-Fi, we expect performance degradations of Wi-Fi networks. In this paper, we quantify the impact of TDM schemes on Wi-Fi performance in a coexistence scenario. We provide an analytical model to compute the probability of collision faced by Wi-Fi and its downlink throughput performance. This model provides an upper bound of the probability of collision that could be faced by a finite number of Wi-Fi stations. NS3 simulations show that the model estimates accurately the collision probability and the throughput experienced by Wi-Fi. The model is then used to study and compare different coexistence schemes showing for instance that the Wi-Fi frame size impacts globally the performance of Wi-Fi users.

Spectrum sharing is a key function to provide fairness allocation as well as service satisfaction across multiple users in cognitive radio networks. Even though spectrum sharing can benefit from spectrum handoff to enhance rate performance by switching from unavailable channels to available ones, the negative impact on handoff delay can cause significant service degradation. In this work, we present a hybrid spectrum sharing strategy that includes novel static and dynamic spectrum sharing algorithms based essentially on a rate compensation approach and adapted best fit algorithms. The static scheme is applicable for some specific network configurations where spectrum handoff is not necessary. Conversely, the dynamic scheme can benefit from spectrum handoff to increase the achieved rate and also compensate for the lost rate from the unavailable periods. These two sharing schemes are operated adaptively according to the current network environment. We compare our hybrid strategy with a fully dynamic one and an optimization framework. The proposed hybrid spectrum sharing demonstrates its effectiveness in terms of improving the overall service satisfaction and reducing the number of handoffs while the achieved rate is fulfilling compared to the optimal.

Sharing available resources in cognitive radio networks can benefit from spectrum handoff to enhance the rate performance by switching from current unavailable channels to the available ones. However, spectrum handoff can cause transmission interruptions leading to the degradation of services. In this work, we aim to balance the tradeoff between benefits of spectrum handoff and their negative impacts on spectrum sharing. Therefore, we develop an adaptive hybrid strategy that includes novel static and dynamic spectrum sharing based essentially on a rate compensation concept. The former is suitable when spectrum handoff is not necessary. The latter allows performing spectrum handoff to compensate the lost rate from the unavailable periods and improve the rate performance. We compare our hybrid strategy with a fully dynamic one and an optimization framework. Through simulations, we show that our strategy reduces the number of handoffs significantly while the achieved rate is fulfilling compared to the optimal.

In this work, we propose a heuristic for dynamic spectrum sharing in cognitive radio networks. The concept of rate compensation is introduced so that cognitive radio users are able to achieve their rate requirement by performing adequately spectrum handoffs. Indeed, performing spectrum handoff can increase the achieved rate obtained by moving from unavailable channels to available ones. However, handoffs should also be reduced to decrease handoff delays and access contention in the network which can in turn impact the achieved rate.

In cognitive radio networks, spectrum sharing among secondary users can benefit from having more transmission opportunities through spectrum handoff. However, the spectrum sharing strategy can also increase negatively the number of performed handoffs. In this work, we study formally the impact of spectrum sharing on spectrum handoff and at the same time the impact of the spectrum handoff on the overall achievable rates from spectrum sharing. We base our study on three proposed spectrum sharing strategies: static, instantaneous and global. We show that depending on the network configuration, static and/or instantaneous can be almost as powerful as the global strategy. In case handoffs are necessary, the global strategy reduces them significantly. Furthermore, we analyze the benefits of multi-channel communications on the quality of sharing in terms of fairness, achieved rate and number of handoffs.

In Cognitive Radio Networks, secondary users are required to handoff from a wireless channel to another in order to cope with the dynamic spectrum environment imposed by primary users activity. Spectrum handoff may cause service interruptions or significant delays leading to the degradation of the quality of transmission. In this paper, we propose and study a novel spectrum handoff strategy aiming at reducing the unnecessary handoff operations while considering a delay bound requirement. First, the expected delay of application packets is computed as a function of the queue associated with a channel. This delay reflects the status of the channel and its usability for transmitting packets. Second, and in order to prevent the unnecessary handoffs, we use the expected delays to estimate a delay violation ratio that guides the spectrum handoff and selection decisions. Besides, we study the utility of using additional backup channels at the time of handoff to alleviate the problem of fast successive handoffs. We show through simulations that our strategy controls better the tradeoff between channel handoffs and achieving the delay requirement compared to random handoff and low channel occupancy handoff.

In Cognitive Radio Networks (CRN), nodes can switch to different operating frequency bands and adapt their transmission power levels such that Cognitive Radio (CR) nodes transmissions remain transparent to the Primary Radios (PR). This constraint can be assured by keeping the aggregated interference caused by CR transmissions at PR nodes location below a defined threshold. In this paper, we propose: (1) A generic framework to assist decentralized power sharing in cognitive radio networks (2) An analytical formulation for optimal power sharing in CRN. We show that managing the placement of the cognitive radio senders plays an essential role in creating a densely connected CRN, even in the presence of multiple primary radios that limit CRs transmission power.

Wireless Mesh Networks are mainly used for providing last-mile broadband wireless access. It is then highly recommended to ensure fairness among different users regardless of their physical locations while increasing their throughput. In this paper, we construct weighted contention graphs for the calculation of maximal capacity per flow and then we search how to maintain fairness per aggregate source-destination flow under bursty traffic. We propose a distributed dynamic contention window algorithm that uses an additional queue per node and we analytically show that our proposal can improve fairness in wireless mesh networks. We also show by simulations on OMNET++ the efficiency of the proposed solution even in bursty conditions. Thanks to the proposed solution, throughput capacity is much more fair compared to basic multihop networks.

Mobile wireless ad hoc networks (MANETs) naturally support a traffic mix of elastic and real-time flows but the shared nature and lossy properties of the radio medium make their coexistence challenging. We argue in this paper for a new kind of elastic data transport service which would preserve the quality of real-time priority flows while guaranteeing an acceptable (tunable) end-to-end delivery time of elastic data. We propose to use mechanisms from Delay Tolerant Networking (DTN) to support hop-by-hop data transfer from source to destination and an adaptation of TCP which monitors its aggressiveness towards local VoIP traffic on each hop. The scheme is evaluated in simulation on a simple 4-node scenario and in a more realistic case where doubling data transfer time allows for the support of seven VoIP flows of medium quality against none for standard TCP.

Sensor networks are prone to congestion due to bursty and high-bandwidth data traffic, combined with wireless links and many-to-one data routing to a sink. Delayed and dropped packets then degrade the performance of the sensing application. In this paper, we investigate the value of separate handling of sensor control and data traffic, during times of congestion, in a closed-loop sensor network. We first show that prioritizing sensor control traffic over data traffic decreases the round-trip control-loop delay, and consequently increases the quantity and quality of the data collected by the sensor network. We then ground our analysis in a closed-loop meteorological sensor network, focusing on a storm-tracking application running over a network of X-band radars. Our application measures reflectivity (a measure of the number of scatterers in a unit volume of atmosphere known as a voxel) and tracks storms (i.e., regions of high reflectivity) using a Kalman filter. Considering data quantity, we show that prioritizing sensor control traffic increases the number of voxels, V, that can be scanned given a constant number of reflectivity samples, Nc, obtained per voxel. Here, utility increases linearly with the number of scanned voxels. Considering data quality, we show that prioritizing sensor control traffic increases the number of reflectivity samples, N, that can be obtained per voxel given a constant number of voxels, Vc, to scan. Here, since sensing accuracy improves only as a function of radicN, the gain in accuracy for the reflectivity estimate per voxel as N increases is relatively small except when prioritizing sensor control increases N significantly (such as when sensor control packets suffer severe delays). Because accuracy also degrades as a function of radicN, however, and because prioritizing sensor control traffic reduces the number of control packets dropped, data degradation is mitigated. Considering the performance of the tracking application, we then show that during times of severe congestion, not prioritizing sensor control can actually lead to tracking errors accumulating over time.

We present a novel routing approach for multichannel cognitive radio networks (CRNs). Our approach is based on probabilistically estimating the available capacity of every channel over every CR-to-CR link, while taking into account primary radio (PR). Our routing design consists of two main phases. In the first phase, the source node attempts to compute the most probable path (MPP) to the destination (including the channel assignment along that path) whose bandwidth has the highest probability of satisfying a required demand D. In the second phase, we verify whether the capacity of the MPP is indeed sufficient to meet the demand at confidence level delta. If that is not the case, we judiciously add channels to the links of the MPP such that the augmented MPP satisfies the demand D at the confidence level delta. We show through simulations that our protocol always finds the best path to the destination, achieving in some cases up to 200% improvement in connection acceptance rate compared to the traditional Dijkstra.

WiMAX mesh mode, recently standardized, enables direct communications between subscriber stations without referring to the base station (BS). It can be a great solution for providing access in hard-to-wire areas and especially in extending the coverage of the BS. In this paper, we propose a joint routing and scheduling algorithm for improving the performance of WiMAX mesh networks in terms of throughput. Our routing algorithm selects highest end-to-end data rate paths for maximizing the network capacity. The scheduling algorithm ensures best scheduling on the selected links for maximizing network utilization, and guarantees fairness as well. We show by numerical simulations that the proposed joint routing and scheduling algorithm, significantly increases the network capacity and utilization while ensuring fairness.

In this paper we present a novel algorithm aiming at connecting members of a community equipped with mobile devices based on their location. Initially, these users are far from each other and they are not able to benefit from the high speed of Wi-Fi ad-hoc mode, and thus they can not exchange real-time media such as streaming music. Based on a centralized server, we employ user locations in order to direct them to new locations where connectivity is available. We distinguish two types of user behavior, cooperative and non-cooperative. The former, follows the commands of movement systematically whereas the latter has its own movement. Our objective then is to maximize the number of connected users while minimizing the traveled distances walked by cooperative users.

A common feature of congestion control protocols is the presence of information packets used to signal congestion. We address here the question of how frequently such protocols need to generate information packets in order to optimize their performance. Through a number of congestion control models, we identify and quantify different types of effects of the frequency of generating information packets. We consider both TCP-type protocols, in which controlling the frequency of information packets is done through static or dynamic delayed ACK options, as well as ATM type flow control, where the optimal time spacing between the generation of network management packets is computed. We show how the spacing between information packets influences the throughput and the stability of the system.

Maintaining fairness in WMNs is quite important but has been given less attention relative to other aspects such as capacity maximization and maintaining connectivity [1]. IEEE 802.11 MAC protocol has been used as the defacto standard for WMNs although it has been initially designed to operate in wireless local area networks. It is known to be unfair in multihop networks. This unfairness is quite evident in bursty conditions which frequently occur in WMNs where subscribers to the same service level must be fairly regarded.

We present HbH a new control paradigm in order to overcome nodes failures in multihop wireless ad hoc networks. HbH is an enhancement of the IEEE 802.11 protocol, that enables packet and buffer control at the MAC layer. Previous works have shown that the use of acknowledgments at the transport layer in multihop wireless networks reduces considerably the goodput achieved by connections. Instead of using end-to-end or hop-by-hop acknowledgements, with HbH wireless nodes track neighbors transmission to know if packets are correctly delivered and to detect nodes failures. The innovation in our work is in pushing down such control to the MAC layer which allows taking advantage of the broadcast nature of the wireless medium. HbH attempts to provide a reasonable trade-off between reliability and performance as well as complexity. Our objective is also to study the effectiveness of providing end-to- end reliability by using hop-by-hop flow control. We compare the performance of our protocol in J-Sim simulator with the traditional IEEE 802.11. We show that we can increase the reliability of a UDP flow without adding control overhead thus increasing the goodput as well.

In this work, we study the performance of the IEEE 802.11 MAC protocol and its impact on the transport layer performance in multihop wireless ad-hoc networks. We focus on the hidden node problem that effects heavily the end-to-end delay and the packet loss probability. Through a mathematical analysis, we compute the packet loss probability as a function of the load. We develop a simplified model of a multihop wireless network and we use it to analyze the interaction between collision and congestion. We find that reducing the size of the MAC output queue can increase the applications throughput. This is done by setting the adequate buffer size that makes congestions and collisions operate in the same region. This will also allow closed or open-loop control protocols such as TCP to react correctly to losses caused by collisions as well as losses caused by buffer overflow. Simulation results with TCP traffic corroborate our theoretical analysis.

With the growing popularity of Web applications, there is a considerable increase in the importance of managing Web sites to deliver high levels of performance and scalability to accommodate future growth and evolution. One of the key issues in this regard concerns a better understanding of the traffic patterns at multiple levels, such as the levels of requests, pages and sessions. This paper presents a detailed analysis of measurement data from various sources pertaining to a specific multi-tiered, geographically distributed architecture that has been used to host the Web sites for a number of recent, popular sporting events. Our analysis of the request-level and page-level patterns demonstrate differences among the Web sites depending upon the type of event and the breadth of interests of the user community. Some of these patterns are consistent with commercial Web sites, while others are significantly different These results further illustrate geographical differences in the request-level and page-level patterns. Our analysis also investigates in detail session-level characteristics. This includes an analysis of the session durations, the think time distributions, the dependence structure of the session arrival process, and the page views comprising each session.

We present an approach to analyzing the performance characteristics of TCP sessions in the presence of network routers which deploy the random early detection (RED) mechanism with two in-and-out drop probability functions (RIO). We consider the case with a large number of TCP sessions which use token buckets for marking in and out packets at the entrance of the network. Under some simplifying assumptions, we derive a set of equations that govern the evolution of these TCP sessions and the routers under consideration. The equations are solved numerically using a fixed point method. Our analysis can capture characteristics of both RED and tail drop (TD) mechanisms in the RIO router. Our model is validated through simulations which show that less than 5% error is achieved in most cases. Various performance analyses are carried out using this approach to study the impact of the RIO parameters on the performance characteristics of TCP sessions. The results show that the loss probability threshold of out packets has a significant effect on the TCP throughput and on the average queue length. Setting this parameter consists of trading off between network utilization and fairness among TCP connections. The results also show that the tail drop mechanism is particularly suitable for use in packets to satisfy various QoS constraints.