Browsing by Author "Noor, Hira"

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Open Access
Load balancing enhancements to the routing protocol for low power and lossy networks in the internet of things
(2018-11) Noor, Hira
The internet today is shifting from the Internet of people to the Internet of Things (IoT). Particularly, in IoTs, wireless sensors connect edge devices to the Internet via a gateway that provides connectivity between wireless sensor networks (WSNs) and the Internet. IoT includes a variety of heterogeneous network applications ranging from smart grid automated metering infrastructures (AMIs), industrial and environmental monitoring networks to building automation. In WSNs, congestion causes a plenty of impairments such as increased packet losses, lower throughput, and energy wastage thus decreasing the lifetime and performance of wireless sensor applications. IPv6 over Low Power Wireless Personal Area Networks (6LoWPAN) is envisioned to be used in the majority of IoT applications. Recently, the Internet Engineering Task Force (IETF) Routing over Low power and Lossy Networks (ROLL) working group has proposed a Routing Protocol for Low power and Lossy networks called RPL. RPL is often studied in a multipoint-to-point sink node (MP2P) scenarios. We investigate the load balancing and congestion problem of RPL. RPL su ers from congestion and unbalanced load distribution due to the use of a single path for multipoint-to-point traffic. In particular, we propose queue utilization-based multipath RPL (QU-MRPL). In QU-MRPL, multiple parents are selected based on their queue size information. We demonstrate that QU-MRPL achieves load balance in the network and thus increases the packet delivery ratio.
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Marsovan theological seminary
(Bilkent University, 2018) Khuseynov, Shukhrat; Manzoor, Ayman; Noor, Hira; Javed, Junaid; Malik, Hammad
Open Access
Online optimization of wireless sensors selection over an unknown stochastic environment
(Institute of Electrical and Electronics Engineers, 2018) Qureshi, Muhammad Anjum; Sarmad, Wardah; Noor, Hira; Mirza, Ali Hassan
Wireless communication is considered to be more challenging than the typical wired communication due to unpredictable channel conditions. In this paper, we target coverage area problem, where a group of sensors is selected from a set of sensors placed in a particular area to maximize the coverage provided to that area. The constraints to this optimization are the battery power of the sensor and number of sensors that are active at a given time. We consider a variant of the coverage related to a particular sensor, where coverage is considered to be an unknown stochastic variable, and hence, we need to learn the best subset of sensors in real time. We propose an online combinatorial optimization algorithm based on multi-armed bandits framework that learns the expected best subset of sensors, and the regret of the proposed online algorithm is sub-linear in time. The achieved performance proves the robustness and effectiveness of the proposed online algorithm in wireless sensor selection over an unknown stochastic environment.