A pro-active mobility management scheme for publish/subscribe middleware systems

Kattepur²,

Proceedings of the 15th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services

et al. 2018

Mobile Internet of Things (IoT) applications are typically deployed on resource-constrained devices with intermittent network connectivity. To support the deployment of such applications, the Publish/Subscribe (pub/sub) interaction paradigm is often employed, as it decouples mobile peers in time and space. Furthermore, pub/sub middleware protocols and APIs consider the Things' hardware limitations and support the development of effective applications by providing Quality of Service (QoS) features. These features aim to enable developers to tune an application by switching different levels of response times and delivery success rates. However, the profusion of pub/sub middleware protocols coupled with intermittent network connectivity result in non-trivial application tuning. In this paper, we model the performance of middleware protocols found in IoT, which are classified within the pub/sub interaction paradigm-both reliable and unreliable underlying network layers are considered. We model reliable and unreliable protocols, by considering QoS semantics for data validity, buffer capacities as well as the intermittent availability of peers. Finally, we perform statistical analysis by varying these QoS semantics, demonstrating their significant effect on the rate of successful interactions. We showcase the application of our analysis in concrete scenarios relating to Traffic Information Management systems, that integrate both reliable and unreliable participants. The consequent PerfMP performance modeling pattern may be tailored for a variety of deployments, in order to control fine-grained QoS policies.

Section: Related Workmentioning

confidence: 99%

Queueing Network Modeling Patterns for Reliable and Unreliable Publish/Subscribe Protocols

Kattepur²,

Proceedings of the 15th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services

et al. 2018

“…Furthermore, in [39] the authors extended the above work by providing closed form expressions of reliability as a function of the number of brokers, transmission range, area dimensions and deadline parameters. Subsequently, Gaddah et al in [23,40], focus on user mobility into the pub/sub interaction paradigm to investigate a pro-active caching approach. Based on this work, to design new hand-off management solutions they consider a fixed network topology where transfer/caching of events/subscriptions between brokers occur prior to subscribers' movement.…”

Section: Related Workmentioning

confidence: 99%

Timeliness Evaluation of Intermittent Mobile Connectivity over Pub/Sub Systems

Proceedings of the 8th ACM/SPEC on International Conference on Performance Engineering

Kattepur

et al. 2017

Systems deployed in mobile environments are typically characterized by intermittent connectivity and asynchronous sending/reception of data. To create effective mobile systems for such environments, it is essential to guarantee acceptable levels of timeliness between sending and receiving mobile users. In order to provide QoS guarantees in different application scenarios and contexts, it is necessary to model the system performance by incorporating the intermittent connectivity. Queueing Network Models (QNMs) offer a simple modeling environment, which can be used to represent various application scenarios, and provide accurate analytical solutions for performance metrics, such as system response time. In this paper, we provide an analytical solution regarding the end-to-end response time between users sending and receiving data by modeling the intermittent connectivity of mobile users with QNMs. We utilize the publish/subscribe (pub/sub) middleware as the underlying communication infrastructure for mobile users. To represent the user's connections/disconnections, we model and solve analytically an ON/OFF queueing system by applying a mean value approach. Finally, we validate our model using simulations with real-world workload traces. The deviations between the performance results foreseen by the analytical model and the ones provided by the simulator are shown to be less than 5% for a variety of scenarios.

“…To extend pub/sub middleware systems operating in the mobile wireless environments, the approach in [22] guarantees that all the published messages are successfully delivered to all interested subscribers in their publishing order regardless of the current location of the mobile subscribers. Here, similarly to our approach, intermittent connectivity period has been taken into account.…”

Section: Related Workmentioning

confidence: 99%

Leveraging CDR datasets for context-rich performance modeling of large-scale mobile pub/sub systems

Agarwal

2015 IEEE 11th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)

et al. 2015

Large-scale mobile environments are characterized by, among others, a large number of mobile users, intermittent connectivity and non-homogeneous arrival rate of data to the users, depending on the region's context. Multiple application scenarios in major cities need to address the above situation for the creation of robust mobile systems. Towards this, it is fundamental to enable system designers to tune a communication infrastructure using various parameters depending on the specific context. In this paper, we take a first step towards enabling an application platform for large-scale information management relying on 'mobile social crowd-sourcing'. To inform the stakeholders of expected loads and costs, we model a large-scale mobile pub/sub system as a queueing network. We introduce additional timing constraints such as (i) mobile user's intermittent connectivity period; and (ii) data validity lifetime period (e.g. that of sensor data). Using our MobileJINQS simulator, we parameterize our model with realistic input loads derived from the D4D dataset (CDR) and varied lifetime periods in order to analyze the effect on response time. This work provides system designers with coarse grain design time information when setting realistic loads and time constraints.