Hengky Susanto

Congestion Control with QoS and Delays Utility Function

This paper primarily addresses how available bandwidth should be optimally distributed among competing streams of elastic traffic like TCP traffic while taking Quality-of-Service (QoS) and delay into consideration. Network Utility Maximization (NUM) in [1], a congestion control algorithm, allows users to set for an optimum network-wide rate allocation through their utility. By incorporating delay into utility function, users can accommodate for QoS requirements.

Pricing and revenue sharing mechanism for secondary redistribution of data service for mobile devices

Cellular Network Providers (CNP) provide users with wireless data access to meet the growing ubiquitous demand for the Internet. As users subscribe to a fixed data plan for a monthly flat fee, some users may exhaust their data allowance before the end of the billing cycle, while others underutilize their monthly quota. To take advantage of such underutilization, Khausik et. al. propose a mechanism for ad hoc bandwidth redistribution that allows subscribers to sell their unused bandwidth to users needing Internet access in exchange for some financial compensation as and when opportunities arise. There exists a popular belief that allowing such on-demand ad hoc service is not beneficial to CNP. This paper seeks to address and counter this opinion by proposing a pricing scheme and a revenue sharing mechanism that makes the provision of ad hoc connection advantageous to CNP. Our revenue sharing mechanism provides economic incentives to CNP. The simulation results show that our revenue sharing model ensures that CNP receives the majority portion of the revenue gained, regardless of the amount. Secondly, our pricing model ensures traffic from ad hoc users has minimal impact on the connection quality of current subscribers. In this model, we use Shapley value as the basis for deriving the revenue sharing.

Congestion control and user utility function for real-time traffic

Usage of multimedia communication in everyday life has seen a remarkable growth. Vast in Bandwidth demand often result in lower network performance and reduced quality of user experience during congestion. In this paper, we will address congestion control problem while providing quality of service (QOS) of delay for inelastic flows like video streaming, IPTV, etc. First, we propose an extension of an existing user utility function to capture users satisfaction over bandwidth allocation, QoS, and the cost to acquire the service. Second, we will study the relationship between these three entities.

Per-Connection Return Routability Test in Mobile IPv6

Abstract – As a mobile node switches from one subnet to another, Mobile IPv6 requires that it authenticate the new Care of Address of the new subnet with the corresponding node. The authentication process, called Return Routability (RR) Test, is required in every handoff and can delay the handoff process by a round trip delay between mobile and corresponding nodes. In this paper, two mechanisms are proposed to reduce the latency involved in RR tests and binding association. They eliminates triangular routing delay in RR tests by using multiple authentication tokens or easily regenerative tokes, so that the round trip delay in performing RR tests can be eliminated.

User Experience Driven Multi-Layered Video Based Applications

The growing popularity for video based applications has put an enormous strain on the network and causes the network to be more prone to congestion. The study of congestion control and bandwidth allocation problems is often formulated into Network Utility Maximization (NUM) framework, and the existing solutions for NUM generally focus on single-layered applications. However, todays quality of video is divided into several layers, where each layer provides different level of enhancement of quality. In this paper, we study how multi-layered video based applications impact network performance and pricing through NUM formulation, in particularly traffic from video streaming. In our investigation, we design and implement a new multi-layered user utility model that leverages on studies of human visual perception. Then, using this new utility model to examine network activities, we demonstrate that solving NUM with multi-layered utility is intractable, and that rate allocation and network pricing may oscillate due to user behavior specific to multi-layered applications. To address this, we propose a new approach for admission control to ensure quality of service and experience.

Modeling Change Without Breaking Promises

Promise theory defines a method by which static service bindings are made in a network, but little work has been done on handling the dynamic case in which bindings must change over time due to both contingencies and changes in policy. We define two new kinds of promises that provide temporal scope for a conditional promise. We show that simple temporally-scoped promises can describe common network behaviors such as leasing and failover, and allow an agent to completely control the sequence of sets of promises to which it commits with another agent, over time. This allows agents to adapt to changing conditions by making short-term bilateral agreements rather than the long-term unilateral agreements provided by previous promise constructions.

Pricing and revenue sharing in secondary market of mobile internet access

There is a fast growing number of public spaces offering Wi-Fi access to meet the rising demands for Internet access. It is common for such service to be offered to users at no charge or for a flat fee. Both situations provide very little incentive for Wi-Fi providers to offer better service to the users. Similarly, Wi-Fi providers pay a monthly flat rate to ISP for Internet access and, this too does not incentivize ISP to offer better service to Wi-Fi users. As a result, Wi-Fi users may experience poor connection when network becomes congested during peak hours. In this paper we propose a dynamic pricing scheme for Internet access and a revenue sharing mechanism that provides incentives for both ISP and Wi-Fi providers to offer better service to their users. We build our revenue sharing model based on Shapley value mechanism. Importantly, our proposed revenue sharing mechanism captures the power negotiation between ISP and Wi-Fi providers, and how shifts in power influences revenue division. Specifically, the model assures that the party who contributes more receives a higher portion of the revenue. In addition, our simulation demonstrates that our model captures the bargaining power shifts between Wi-Fi providers and ISP, and shows that the division of revenue asymptotically converges to a percentage value.

Message passing delay in network congestion management

Network Utility Maximization (NUM) framework has been extensively studied. Generally, existing solutions for NUM require message exchange between network and users to regulate the flow of network traffic, and information is frequently assumed to be available instantaneously and the traffic flow adjustment is accomplished immediately. However, realistically, there is delay in message exchange because time is required for the messages to reach the designated destinations and for the traffic flow adjustment in network to take effect. Consequently, without proper synchronization, transmission rate and network pricing may oscillate, resulting in the algorithms failure to converge, even when there is a solution that converges to an optimal solution. Here, we propose a synchronization methodology to prevent the algorithm from oscillating.

Effective Mobile Data Trading in Secondary Ad-hoc Market with Heterogeneous and Dynamic Environment

Advances in smartphone technologies enable mobile data subscribers to resell their data allowance to other users, creating a secondary data market. The trading environment of this secondary data market is dynamic and ad-hoc: buyers and sellers join and leave the market at all times, changing the trading landscape constantly. The amount of data demanded and offered at any point in time also vary. These conditions make determining a fair transaction price, and matching buyers to sellers difficult in practice. Prior schemes utilize global description of the network and market forces to achieve good performance, but the implementation requires a high overhead cost. In this paper, we present DataMart, a data pricing and user matching platform for trading in this dynamic, ad-hoc and heterogeneous market that works in distributed manner without needing global information. Using insights from real world traces, we demonstrate via simulation that our pricing scheme is converging and consistent with the law of demand and supply. Further, our user matching scheme achieves comparable performance to the optimal solution. We implement a prototype on Android platform, and the experiment results confirm the effectiveness of DataMart.

Secondary Market Mobile Users for Internet Access

There is a fast growing number of public spaces offering Wi-Fi access to meet the rising demands for the Internet. It is common for such service to be offered to users at no charge or for a flat fee. Both situations provide very little incentive for Wi-Fi providers to offer better service to the users. Similarly, Wi-Fi providers pay a monthly flat-rate to ISP for Internet access, which does not incentivize ISP to offer better service to Wi-Fi users. As a result, Wi-Fi users may experience poor Internet connection when network becomes congested during peak hours. In this paper, we propose a dynamic pricing mechanism for both ISP and Wi-Fi providers in order to give mobile Wi-Fi users better service, while providing economic incentive for both ISP and Wi-Fi provider.