Near-Optimal Packet Scheduling in Multihop Networks with End-to-End Deadline Constraints

Scheduling packets with end-to-end deadline constraints in multihop networks is an important problem that has been notoriously difficult to tackle. Recently, there has been progress on this problem in the worst-case traffic setting, with the objective of maximizing the number of packets delivered within their deadlines. Specifically, the proposed algorithms were shown to achieve $\Omega(1/\log(L))$ fraction of the optimal objective value if the minimum link capacity in the network is $C_{\min}=\Omega(\log (L))$, where $L$ is the maximum length of a packet's route in the network (which is bounded by the packet's maximum deadline). However, such guarantees can be quite pessimistic due to the strict worst-case traffic assumption and may not accurately reflect real-world settings. In this work, we aim to address this limitation by exploring whether it is possible to design algorithms that achieve a constant fraction of the optimal value while relaxing the worst-case traffic assumption. We provide a positive answer by demonstrating that in stochastic traffic settings, such as i.i.d. packet arrivals, near-optimal, $(1-\epsilon)$-approximation algorithms can be designed if $C_{\min} = \Omega\big(\frac{\log (L/\epsilon) } {\epsilon^2}\big)$. To the best of our knowledge, this is the first result that shows this problem can be solved near-optimally under nontrivial assumptions on traffic and link capacity. We further present extended simulations using real network traces with non-stationary traffic, which demonstrate that our algorithms outperform worst-case-based algorithms in practical settings

A New Competitive Ratio for Network Applications with Hard Performance Guarantee

Online algorithms are used to solve the problems which need to make decisions without future knowledge. Competitive ratio is used to evaluate the performance of an online algorithm. This ratio is the worst-case ratio between the performance of the online algorithm and the offline optimal algorithm. However, the competitive ratios in many current studies are relatively low and thus cannot satisfy the need of the customers in practical applications. To provide a better service, a practice for service provider is to add more redundancy to the system. Thus we have a new problem which is to quantify the relation between the amount of increased redundancy and the system performance. In this dissertation, to address the problem that the competitive ratio is not satisfactory, we ask the question: How much redundancy should be increased to fulfill certain performance guarantee? Based on this question, we will define a new competitive ratio showing the relation between the system redundancy and performance of online algorithm compared to offline algorithm. We will study three applications in network applications. We propose online algorithms to solve the problems and study the competitive ratio. To evaluate the performances, we further study the optimal online algorithms and some other commonly used algorithms as comparison. We first study the application of online scheduling for delay-constrained mobile offloading. WiFi offloading, where mobile users opportunistically obtain data through WiFi rather than through cellular networks, is a promising technique to greatly improve spectrum efficiency and reduce cellular network congestion. We consider a system where the service provider deploys multiple WiFi hotspots to offload mobile traffic with unpredictable mobile users’ movements. Then we study online job allocation with hard allocation ratio requirement. We consider that jobs of various types arrive in some unpredictable pattern and the system is required to allocate a certain ratio of jobs. We then aim to find the minimum capacity needed to meet a given allocation ratio requirement. Third, we study online routing in multi-hop network with end-to-end deadline. We propose reliable online algorithms to schedule packets with unpredictable arriving information and stringent end-to-end deadline in the network

A New Competitive Ratio for Network Applications with Hard Performance Guarantee

Online algorithms are used to solve the problems which need to make decisions without future knowledge. Competitive ratio is used to evaluate the performance of an online algorithm. This ratio is the worst-case ratio between the performance of the online algorithm and the offline optimal algorithm. However, the competitive ratios in many current studies are relatively low and thus cannot satisfy the need of the customers in practical applications. To provide a better service, a practice for service provider is to add more redundancy to the system. Thus we have a new problem which is to quantify the relation between the amount of increased redundancy and the system performance. In this dissertation, to address the problem that the competitive ratio is not satisfactory, we ask the question: How much redundancy should be increased to fulfill certain performance guarantee? Based on this question, we will define a new competitive ratio showing the relation between the system redundancy and performance of online algorithm compared to offline algorithm. We will study three applications in network applications. We propose online algorithms to solve the problems and study the competitive ratio. To evaluate the performances, we further study the optimal online algorithms and some other commonly used algorithms as comparison. We first study the application of online scheduling for delay-constrained mobile offloading. WiFi offloading, where mobile users opportunistically obtain data through WiFi rather than through cellular networks, is a promising technique to greatly improve spectrum efficiency and reduce cellular network congestion. We consider a system where the service provider deploys multiple WiFi hotspots to offload mobile traffic with unpredictable mobile users’ movements. Then we study online job allocation with hard allocation ratio requirement. We consider that jobs of various types arrive in some unpredictable pattern and the system is required to allocate a certain ratio of jobs. We then aim to find the minimum capacity needed to meet a given allocation ratio requirement. Third, we study online routing in multi-hop network with end-to-end deadline. We propose reliable online algorithms to schedule packets with unpredictable arriving information and stringent end-to-end deadline in the network

Quality-of-service in wireless sensor networks: state-of-the-art and future directions

Wireless sensor networks (WSNs) are one of today’s most prominent instantiations of the ubiquituous computing paradigm. In order to achieve high levels of integration, WSNs need to be conceived considering requirements beyond the mere system’s functionality. While Quality-of-Service (QoS) is traditionally associated with bit/data rate, network throughput, message delay and bit/packet error rate, we believe that this concept is too strict, in the sense that these properties alone do not reflect the overall quality-ofservice provided to the user/application. Other non-functional properties such as scalability, security or energy sustainability must also be considered in the system design. This paper identifies the most important non-functional properties that affect the overall quality of the service provided to the users, outlining their relevance, state-of-the-art and future research directions

Reactive GTS Allocation Protocol for Sporadic Events Using the IEEE 802.15.4

Wireless sensor networks (WSNs) find applications in the industrial automation where periodic and sporadic events occur. The combined propagation of information generated by periodic and sporadic events from a sensor node to an actuator node is challenging due to random nature of sporadic events, particularly, if the deadlines are hard. The IEEE 802.15.4 standard provides the basis for a real-time communication mechanism between neighboring nodes of the WSN at the media access control layer. However, the standard does not address such communications over multiple hops. To support the industrial applications with such requirements, this work proposes a novel online control protocol that exploits the basis provided by the IEEE 802.15.4 standard. The proposed control protocol ensures that a given offline sporadic schedule can be adapted online in a timely manner such that the static periodic schedule has not been disturbed and the IEEE 802.15.4 standard compliance remains intact. The proposed protocol is simulated in OPNET. The simulation results are analyzed and presented in this paper to prove the correctness of the proposed protocol regarding the efficient real-time sporadic event delivery along with the periodic event propagation