Showing papers presented at "IFIP Wireless Days in 2014"

Wireless contacts, Facebook friendships and interests: Analysis of a multi-layer social network in an academic environment

Abstract: Human mobility traces have drawn increasing attention in recent years due to their usefulness for constructing mobility models and evaluating mobile opportunistic communication systems. Even if human mobility provides us insights into the social behavior of mobile users, there is a growing awareness that human sociality is expressed simultaneously on multiple layers. The multilayered complex network composed by the social network constructed on wireless contacts and other types of social network layers needs still to be analyzed and understood in depth. In this paper, we describe the experiment we performed in a campus environment to trace the wireless contacts in terms of Bluetooth encounters, occurring between nodes inside and outside the group of experimenters carrying smartphones, and to gather the profiles, Facebook friendships, and interests of the participants. By analyzing the multilayer social network constructed on this dataset, we contribute to novel understanding of human behavior at different social dimensions. We study the relationship between offline encounters detected through mobile devices, Facebook friendships and shared interests in terms of closeness between the corresponding social graphs, matching between strong offline ties and the other social ties, and similarity between communities. We show that Bluetooth contacts network layer and Facebook friendships network layer are similar.

Characteristic utilities, join policies and efficient incentives in Mobile Crowdsensing Systems

Abstract: In this paper we identify basic design issues of Mobile Crowdsensing Systems (MCS) and investigate some characteristic challenges. We define the basic components of an MCS - the Task, the Server and the Crowd - and investigate the functions describing/governing their interactions. We identify three qualitatively different types of Tasks; a) those whose added utility is proportional to the size of the Task, b) those whose added utility is proportional to the progress of the Task and c) those whose added utility is reversely proportional to the progress of the Task. For a given type of Task, and a finite Budget, the Server makes offers to the agents of the Crowd based on some Incentive Policy. On the other hand, each agent that receives an offer decides whether it will undertake the Task or not, based on the inferred cost (computed via a Cost function) and some Join Policy. In their policies, the Crowd and the Server take into account several aspects, such as the number and quality of participating agents, the progress of execution of the Task and possible network effects, present in real-life systems. We evaluate the impact and the performance of selected characteristic policies, for both the Crowd and the Server, in terms of Task execution and Budget efficiency of the Crowd. Experimental findings demonstrate key performance features of the various policies and indicate that some policies are more effective in enabling the Server to efficiently manage its Budget while providing satisfactory incentives to the Crowd and effectively executing the system Tasks. Interestingly, incentive policies that take into account the current crowd participation achieve a better trade-off between Task completion and budget expense.

A strategy for opportunistic cognitive channel allocation in wireless Internet of Things

Abstract: This article presents a strategy for channel assignment in Internet of Things (IoT) networks. The proposed strategy uses opportunistic spectrum access via cognitive radios. The originality of this work resides in the use of traffic history to guide the channel allocation in a distributed manner. The channel assignment algorithm mitigates the interference in links with higher traffic history. Our performance evaluation shows that using the historical network traffic as a decision criterion leads to better results when compared with the simple use of the network topology as a criterion.

YouTube in the move: Understanding the performance of YouTube in cellular networks

Abstract: YouTube is the most popular and volume-dominant service in today's Internet, and is changing the way ISPs manage their networks. Understanding the performance of YouTube traffic is paramount for ISPs, specially for mobile operators, who must handle the huge surge of traffic with the constraints and challenges of cellular networks. In this paper we present an empirical analysis of the performance of YouTube flows accessed through a national-wide cellular network, considering download throughput as well as end-user Quality of Experience (QoE) metrics. The analysis considers the characteristics and impacts of the Content Delivery Network hosting YouTube, and compares its behavior with other popular HTTP video streaming services accessed through cellular networks. The QoE analysis is performed through end-user device measurements, which directly reflect the experience of the end-users. Our study additionally shows the potentiality of monitoring YouTube performance in cellular networks directly from the smart-phones of the users, bypassing the traffic visibility loss at the core of the network introduced by traffic encryption (e.g., HTTPS).

On the performance of hybrid ARQ schemes for uplink information transmission with wireless power transfer in the downlink

Abstract: We investigate a form of energy harvesting consisting of gathering energy from the radio frequency (RF) electromagnetic waves, also know as wireless power transfer. We employ a time switching (TS) protocol to coordinate the harvesting process, which separates a time slot into two parts, one devoted to wireless energy transfer and the other to wireless information transmission. The fraction of time devoted to each task, the TS parameter, has great impact on the overall performance. This paper presents an investigation on the usage of the TS protocol, including the numerical optimization of the TS parameter, when hybrid automatic retransmission (HARQ) schemes are used for information transmission. Our results demonstrate that HARQ schemes can improve the system performance for high SNR. This improvement is even better if if the destination applies Chase combining among the previously received copies of a frame.

Disaster detection in magnetic induction based wireless sensor networks with limited feedback

Abstract: The use of magnetic induction (MI) based transmissions in challenging environments has been investigated in various works. Recently, a system model has been proposed, which explains how the MI based transmission channel depends on the chosen system parameters. In order to make the system robust against environmental changes, the system parameters like resonance frequency and modulation scheme need to be properly adapted to the current channel state. It is frequently assumed, that perfect channel state information (CSI) is available at the transmitter and at the receiver. However, in practical systems this knowledge may not always be easily acquired. In addition, a permanent feedback signaling is needed in order to update the CSI at the transmitter, which usually causes interference to the surrounding devices and reduces the energy efficiency. In this paper, we investigate the potential of a recently proposed approach for channel estimation within the MI transmitter circuit without explicit feedback signaling of CSI. This technique seems promising especially for disaster detection in wireless underground sensor networks, which is the main focus of this work.

Enhanced opportunistic random linear source/network coding with cross-layer techniques over wireless mesh networks

Abstract: In this paper we thoroughly study, by means of simulation, the combination of source and network random linear coding to provide reliable communications over wireless mesh networks. We assume that intermediate nodes code the packets they have previously stored before forwarding them. We also analyze the possibilities that are brought about by opportunistic listening and forwarding, combining them with the use of cross-layer information. We study the performance of the proposed scheme by means of an extensive simulation campaign carried out over the ns-3 platform; the results show that the coding functionality at the intermediate nodes leads to additional performance enhancements. In addition, they also demonstrate the potential benefits of integrating cross-layer techniques.

Assisting V2V failure recovery using Device-to-Device communications

Abstract: This paper aims to propose a new solution for failure recovery (dead-ends) in Vehicle to Vehicle (V2V) communications through LTE-assisted Device-to-Device communications (D2D). Based on the enhanced networking capabilities offered by Intelligent Transportation Systems (ITS) architecture, our solution can efficiently assist V2V communications in failure recovery situations. We also derive an analytical model to evaluate generic V2V routing recovery failures. Moreover, the proposed hybrid model is simulated and compared to the generic model under different constrains of worst and best cases of D2D discovery and communication. According to our comparison and simulation results, the hybrid model decreases the delay for alarm message propagation to the destination (typically the Traffic Control Center TCC) through the Road Side Unit (RSU).

Accurate 2-D localization of RFID tags using antenna transmission power control

Abstract: Localization of tagged objects with sufficient precision is a main issue in many industrial applications. In this paper, a new approach is proposed for the localization of UHF passive tags simply using the environment learning approach. This method uses, for a given passive tag located in a 2-D space, an aggregate function of the Received Signal Strength Indicator (RSSI) for all the possible RFID reader's transmission powers. Based on these measurements, we define a location signature, which is compared with those of other tags located at known positions in the neighborhood. We then implement a method based on the k-Nearest Neighbor (k-NN) algorithm to estimate the position of the target tag. Using a realistic test case involving seventy tags and four antennas, we show a very significant improvement of the localization accuracy in comparison with the results obtained using a single RSSI value.

Dynamic DRX algorithms for reduced energy consumption and delay in LTE networks

Abstract: The Long Term Evolution (LTE) standard specifies the Discontinuous Reception Mechanism (DRX) mechanism for saving power at the User Equipment (UE). Here, a UE switches off its RF circuitry when there are no packets to be transmitted or received. The existing DRX algorithms use static operational parameters that are determined by the evolved nodeB (eNB) at the start of a UE's session. During the switch-off period, packets destined to the UE are buffered in the eNB leading to higher packet latency. This paper presents two adaptive algorithms to dynamically adjust the DRX parameters, in order to reduce both energy consumption and the extra delay incurred. The algorithms use application Quality-of-Service (QoS) and Channel Quality Information (CQI) to adjust the DRX parameters. Performance studies based on ns3 simulator show that the algorithms are able to reduce packet delay compared to static DRX by up to 60%, 60% and 75% and reduce energy consumption by up to 75%, 43% and 90% for video streaming, VoIP and bursty data applications respectively.

Access Point discovery in 802.11 networks

Abstract: This paper analyzes the scanning process in IEEE 802.11 networks in an urban setting characterized by a high Access Point (AP) density. Most of these APs belong to a community network, known as a collection of APs announcing the same network name (Service Set Identifier or SSID). The owner of an AP can optionally configure the community network of his/her AP, resulting in an irregular topology for each community network as there is no central planning authority. We investigate the relationship between the time spent in each channel while scanning for available APs and the number of AP actually detected. In particular we show that, in order to discover all available APs at a given location, we need to combine the results of multiple scans. Based on this result we argue that the efficiency of the scanning process could be greatly improved by using a database shared by all the users of a community network, containing the available APs at different locations.

Evaluating management architectures for Internet of Things devices

Abstract: The Internet of Things (IoT) is foreseen as a global network infrastructure that provides wireless communication among any kind of objects. One immediate challenge holds: how to manage these objects, considering that they may have limited computational resources. This management can be achieved through the use of gateways, i.e., devices that intermediate wireless communications, minimizing resource consumption of the restrained objects. The communication between gateways and objects can be performed over many architectures. Among these architectures, we highlight the Simple Network Management Protocol (SNMP), the Service Oriented Architecture (SOA), and the Resource Oriented Architecture (ROA). However, there is a lack of deeper investigations to define which is the best architecture to model the communication between gateways and objects. Therefore, the main contribution of this paper is a quantitative evaluation of SNMP, SOA, and ROA as means for the communication between gateways and objects. Results analysis pointed ROA as the most interesting architecture to model the management communication.

Implementation of a routing protocol for ad hoc networks in search and rescue robotics

Abstract: As robotics evolves, we expect to see increasing numbers of search and rescue teams (SARTs) of humans and autonomous mobile robots, especially in hazardous scenarios. Under these conditions, a third party infrastructure network might be unavailable, forcing the agents' mobile devices to self-organize in a wireless ad hoc network. Search and rescue actions pose specific challenges to these networks, as they need large communication bandwidths, and, at the same time, a very tight connection to the Command Center (CC). Hence, SART ad hoc networks are neither typical mobile ad hoc networks (MANETs), nor wireless sensor networks with firm energy restrictions. To respond to these requirements, we propose a routing protocol, called CHOPIN, that defines a tree rooted at the CC, while also allowing flooding within teams of nodes. We conceived, implemented and integrated this protocol in the Robot Operating System (ROS), using simple but proven methods, and open standards for messages. The field benchmarking we did against the Optimized Link State Routing Protocol (OLSR) shows the ability of CHOPIN to assist SART agents in their communication.

Towards the enhancement of UAV video transmission with motion intensity awareness

Abstract: The use of video-equipped Unmanned Aerial Vehicles (UAV) has been increasing recently, along with the number of available applications for military and civilian employment. This unveils the need for an adaptive video-aware mechanism capable of overcoming a number of challenges related to the scarce network resources, device movement, as well as high error rates, to ensure a good video quality delivery. Forward Error Correction (FEC) techniques can be tailored to provide adaptive protection with Quality of Experience (QoE) assurance over error-prone and high-mobility networks. Besides that, unique characteristics of each video sequence, such as the spatial complexity and the temporal intensity, strongly affect how the QoE will be impacted by the packet loss. This paper proposes an adaptive motion intensity and video-aware FEC mechanism with the aid of Fuzzy logic to safeguard UAV real-time video transmissions against packet loss, providing a better user experience, while saving resources. The advantages and drawbacks of the proposed mechanism in comparison to the related work are evidenced through experiments and assessed by using QoE metrics.

The failure of CSMA in emerging wireless network scenarios

Abstract: The current family of 802.11 protocols are based on the Carrier Sense Multiple Access (CSMA) mechanism which is a simple and robust means of sharing a channel. However, two current trends in wireless networks point towards a situation where CSMA fails to perform better than pure random access solutions such as ALOHA. The first trend is the ever increasing raw data rate in each generation of 802.11 which is set to continue with the current 802.11ax standardisation. The second is the move towards smaller frames as end users increasingly use mobile devices instead of desktop computers. We show that as the ratio of propagation delay to packet transmission time increases, the performance of CSMA degrades correspondingly, to the point where ALOHA outperforms CSMA.

Joint power-delay minimization in 4G wireless networks

Abstract: In this paper, we formulate an optimization problem that jointly minimizes the network power consumption and transmission delay in broadband wireless networks. Power saving is achieved by adjusting the operation mode of the network Base Stations (BSs) from high transmit power levels to low transmit levels or switched-off. Minimizing the transmission delay is achieved by selecting the best user association with the BSs. We study the case of a realistic Long Term Evolution (LTE) Network where the challenge is the high computational complexity necessary to obtain the optimal solution. Therefore, we propose a simulated annealing based heuristic algorithm for the power-delay minimization problem. The proposed heuristic aims to compute the transmit power level of the network BSs and associate users with these BSs in a way that jointly minimizes the total network power and the total network delay. The simulation results show that the proposed algorithm has a low computational complexity which makes it advantageous compared with the optimal scheme. Moreover, the heuristic algorithm performs close to optimally and outperforms the existing approaches in realistic 4G deployments.

VANETs signal quality-based route selection in smart cities

Abstract: In road networks, the most common metrics to determine the optimal route relaying two points are either the path length or the travel time. However, as autonomous smart cars are expected to emerge in future smart cities and lead to an unprecedented growth of mobile applications spectrum for both drivers and passengers, we argue that other metrics can be also considered for route selection. Therefore, the best route for a driver will be also determined by specific in-vehicle users' requirements such as, ensuring sufficient quality for wireless connection with minimum cost, and selecting preferred access networks, etc. To this end, we propose an original algorithm that enables route selection based on maximum expected signal quality with respect to the drivers' maximum tolerated prolongation of journey. Our ultimate objective is to select the route that ensures sufficient signal quality for users on board by maximizing the usage of VANETs resources, through RSUs, while minimizing the usage of the costly LTE-A resources. The obtained simulation results, under several scenarios, have proven the high efficiency of the proposed algorithm.

Using a token approach for the MAC layer of linear sensor networks: Impact of the node position on the packet delivery

Abstract: Wireless sensor networks (WSNs) consist of a large number of sensor nodes which communicate via wireless links for monitoring applications. In several applications, such as the monitoring of pipelines or roads, the network topology is linear. This type of WSN is called linear sensor network (LSN). Our goal is to improve the behavior of a MAC protocol for LSNs, by using a token approach. As usual, the possession of the token grants the node permission to transmit on the medium during a given amount of time. The payload of the token is used to propagate network parameters such as delay between tokens, sleep and wakeup calendar. In this paper, we study the behavior of this MAC protocol and we evaluate the impact of the node position on the packet delivery for two types of LSNs.

Enhanced multi-channel MAC protocol for multi-hop wireless sensor networks

Abstract: In this paper, we address the challenge of achieving high throughput with limited number of channels in a wireless sensor network (WSN). The use of multiple channels helps overcome, on one hand, interference generated from inner network activity, and on the other hand, interference caused by neighboring systems operating in the same frequency band. We propose a multi-channel MAC protocol with multi-interface nodes for WSNs. In our proposition, we enhance the channel allocation method of HMC-MAC in order to take into account a multi-interface sink and network segmentation into two groups of nodes. We evaluate our protocol using NS2 simulator with different number of available channels in order to emulate a limited number of interference-free channels. Results show that our MAC protocol improves the overall network performance compared to other protocols with limited number of channels and high data rate traffic.

Enhanced connectivity for robust multimedia transmission in UAV networks

Abstract: The usage of Unmanned Aerial Vehicle (UAV) networks has stimulated the development of new multimedia applications due to their high degree of mobility and versatility. Although the transmission of data on UAVs using geographic protocols enables better data delivery rate, it is not enough to provide quality of experience (QoE). This happens due to the high mobility degree of UAVs, occurring thus broken links during the transmission. Those broken links damage the connectivity and cause delays and packet loss. This paper proposes a mechanism, called ECORA, to enhance the routing decision making on geographic protocols, and thus improving the connectivity of UAV networks. ECORA takes into account the positioning prediction and link expiration time. In order to assess the gains with ECORA, it was added to the GPSR protocol and evaluated by simulation experiments. Results show that ECORA favored GPSR to obtain higher delivery packets and lower end-to-end delay, as well as better video quality delivered.

QoS support for bursty traffic in noisy channel via periodic reservations

Abstract: The growth of the number of devices working at the same area, overlapping networks and multihop data transmission degrade the efficiency of contention based channel access. A number of deterministic channel access methods introduced in recent Wi-Fi standards allow to reserve a set of periodical time intervals, during which a single station can access channel without contention. Providing collision free transmission, these methods are favourable for real-time multimedia traffic which demands high quality of service (QoS). However, QoS provisioning for multimedia transmission is significantly complicated by the bursty nature of multimedia traffic and random noise inherent to wireless channels. In this paper, we propose an analytical model of multimedia transmission via periodic reservations considering both multimedia traffic bursty nature and random noise. The model can be used to find reservation parameters which allow to meet QoS requirements while transmitting multimedia data.

Towards localization of RFID tags based on experimental analysis of RSSI

Abstract: RFID has been developed for many applications such as object identification, object traceability, geometric localization, etc. In order to locate an object labeled by a tag, several characteristics of the tag responses have been studied. This yielded theoretical models whose accuracy is not sufficient in practice for targeted applications. In this paper, we investigate how to localize a tag based on the set of received signal strength indicator (RSSI) values measured for a large range of transmission powers. Using an extensive measurement campaign, we establish that the RSSI is a linear function of the transmission power of the RFID reader. Moreover, a minimum transmission power is necessary for activating the tag which also depends on its localization. As a result, the statistics of the RSSI for different transmission powers may be synthetized through a triple. We then show how this triple may be exploited for localizing a tag.

A scheme for using closest rendezvous points and Mobile Elements for data gathering in wireless sensor networks

Abstract: A variety of wireless sensor network (WSN) applications have been proposed. However, the efficiency of WSNs, as well as their ability to interact with different environments, varies. Many challenges and problems to be solved remain. Overcoming these challenges requires a protocol that will design and provide a highly efficient system, thus helping the WSN to transmit data in a suitable time. In WSNs with Mobile Elements (MEs), the task is first to find an effective way to minimize the length of the tour that the ME follows for data gathering. However, the minimized tour length should still offer access to all nodes in the networks for data collection form the sensor nodes. In this paper, we propose a protocol that results in a shorter ME tour length than previously proposed protocols, using closest rendezvous points (CRPs) distributed throughout the network. Furthermore, this proposed protocol offers access to all nodes inside the network for the exchange of data with the MEs, as facilitated by the suggested CRP algorithm. One or more nodes can be represented by a single CRP that provides connectivity to all of the nodes within its wireless range. In cases where a greater number of MEs are used, less time is required to traverse the network for data gathering. This research demonstrates that the tour time can be reduced significantly by using more than one ME.

Interference analysis in cooperative multi-hop networks subject to multiple flows

Abstract: This paper studies the effects of allowing multiple packets to flow simultaneously in a cooperative multi-hop transmission system. Although, the packet delivery rate may increase with multiple packet flows, however, the desired signals of one packet may get interfered with the signals of the other packets in the network, thereby causing some of the packets to die off. This phenomenon is analyzed by modeling the multi-hop transmission as a conditional Markov process, followed by the derivation of its transition matrix. The resulting distribution is used to calculate the outage probability of a node in a cooperative environment in the presence of desired as well as interfering signals. The model is then used to obtain the network coverage, until which a packet can travel for a given packet delivery ratio constraint. Numerical simulations are performed to validate the analytical models.

Software-defined vehicular backhaul

Abstract: The network of roads and highways is a promising candidate to help network operators offload their infrastructure and cope with the ever-growing amount of data exchanged on the Internet. By piggybacking data onto vehicles, roads can be turned into a large-capacity transmission system when considering the increasing number of journeys involving vehicles. The data to be transferred is opportunistically loaded on or off the vehicles at specific locations referred to as offloading spots. Two of the main challenges of such a system are how to assign the road paths matching the data transfer requirements and how much data to allocate to each flow of vehicles. We propose a centralized SDN-like architecture consisting of a central controller acting as a service broker and the offloading spots as SDN agents. The controller computes the road paths that accommodate the data transfer requirements and installs the corresponding forwarding states at each offloading spot along those paths. We describe our SDN-controlled offloading system and evaluate its performance using road traffic counts from France. Our numerical results show that the controller can achieve efficient and fair allocation of multiple data transfers between major cities of France. Each transfer successfully delivers over 10 PB of data within a week when considering that 10% of vehicles on the road are equipped with 1TB of storage.

Data Aggregation for group communication in Machine-to-Machine environments

Abstract: The energy resources of Machine-to-Machine (M2M) devices need to last as much as possible. Data aggregation is a suitable solution to prolong the network lifetime, since it allows the devices to reduce the amount of data traffic. In M2M systems, the M2M platform and the Constrained Application Protocol (CoAP) enable multiple entities to send concurrent data-requests to the same capillary network. For example, in a Smart Metering scenario, there are devices measuring the electricity consumption of an entire building. The supplier company requests all devices to send the data updates every 1800 seconds (i.e., 30 minutes). On the other hand, a resident requests his/her devices to communicate every 600 seconds (i.e., 10 minutes). These concurrent data-requests create heterogeneous groups over the same capillary network, since each group might be able to execute different in-network functions and to have a unique temporal-frequency of communication. However, the traditional data aggregation solutions designed for periodic monitoring assume the execution of a single static data-request during all network lifetime. This makes the traditional data aggregation solutions not suitable for M2M environments. To fill this gap, this paper presents Data Aggregation for Multiple Groups (DAMiG), which is designed to provide Data Aggregation for heterogeneous and concurrent sets of CoAP data-requests. DAMiG explores the group communication periodicity to perform internal and external-group traffic aggregation. To achieve that, DAMiG computes a suitable aggregation structure and applies statistical and merger aggregation functions along the path. DAMiG is able to reduce the energy consumption in scenarios with single or several concurrent CoAP data-requests. Moreover, the selection of internal and external-group paths takes into account the residual energy of the nodes, avoiding the paths with low residual energy.

Comparative performance study of LTE uplink schedulers for M2M communication

Abstract: The Long Term Evolution (LTE) standard is one of the most promising technologies of wireless network for the development of Machine-to-Machine (M2M) communication because of its high data rates, low latency, high flexibility and low cost. However, improvements are needed in the network to support the uplink-heavy traffic generated by M2M communication and also to ensure the diversity of service requirements of this communication. The uplink packet scheduler is included in the necessary improvements. In this article, we evaluate the performance of the main schedulers for M2M communication regarding the aspects of service requirements, fairness, energy efficiency and impact on the system performance of current LTE traffic.

A statistical learning reputation system for opportunistic networks

Abstract: Contacts are essential to guarantee the performance of opportunistic networks, but due to resource constraints, some nodes may not cooperate. In reputation systems, the perception of an agent depends on past observations to classify its actual behavior. Few studies have investigated the effectiveness of robust learning models for classifying selfish nodes in opportunistic networks. In this paper, we propose a distributed reputation algorithm based on the game theory to achieve reliable information dissemination in opportunistic networks. A contact is modeled as a game, and the nodes can cooperate or not. By using statistical inference methods, we derive the reputation of a node based on learning from past observations. We applied the proposed algorithm to a set of traces to obtain a distributed forecasting base for future action when selfish nodes are involved in the communication. We evaluate the conditions in which the accuracy of data collection becomes reliable.

Energy-efficient architecture for wearable sensor networks

Abstract: Human activity recognition from on-body sensor networks is a challenging task for many healthcare applications because it offers continuous monitoring capability. However, these systems still face a major energy issue that prevent their wide adoption. Indeed, in healthcare applications, continuous sampling and communication tasks quickly deplete sensors' battery reserves, and frequent battery replacement are not convenient. Therefore, there is a need to develop energy-efficient solutions for long-term monitoring applications in order to foster the acceptance of these technologies by the patients. In this paper, we present a new energy-efficient architecture for health monitoring where sensors send the sensed data mainly via the user mobile phone, but they have the possibility to send data to access points when they are available in the user environment. The objective of this strategy is to relieve a unique base station from receiving all the data, and it enables sensor nodes to select the best communication technology in terms of energy consumption. Contrary to existing approaches, our solution allows to optimize the lifetime of both the sensor and the base station. The simulation results show that the proposed approach effectively improves the energy efficiency of the system compared to traditional architectures where wearable sensors can only communicate with the user mobile phone.

WiBus: A Wi-Fi based monitoring system for public transportation with dynamic route tracking

Abstract: A great challenge of today's metropolises is the constant traffic jams, which are a consequence of excessive use of private vehicles. More people would adopt public transportation, e.g. buses, if the time of arrival (ToA) for the next vehicle to each bus stop could be predicted. In this direction, we propose WiBus, which is a system to estimate the buses ToA, based on information from opportunistic IEEE 802.11 contacts. Unlike previous systems, WiBus explicitly takes into account bus route changes, adjusting the routes with an algorithm for dynamic route creation and maintenance. The system is implemented and analyzed via emulation of a real scenario. Experimental results show that WiBus has accumulated error of at most a few minutes.