Behnam Attaran Rezaei

Capacity constraints and the inevitability of mediators in adword auctions

One natural constraint in the sponsored search advertising framework arises from the fact that there is a limit on the number of available slots, especially for the popular keywords, and as a result, a significant pool of advertisers are left out. We study the emergence of diversification in the adword market triggered by such capacity constraints in the sense that new market mechanisms, as well as, new for-profit agents are likely to emerge to combat or to make profit from the opportunities created by shortages in ad-space inventory. We propose a model where the additional capacity is provided by for-profit agents (or, mediators), who compete for slots in the original auction, draw traffic, and run their own sub-auctions. The quality of the additional capacity provided by a mediator is measured by its fitness factor. We compute revenues and payoffs for all the different parties at a symmetric Nash equilibrium (SNE) when the mediator-based model is operated by a mechanism currently being used by Google and Yahoo!, and then compare these numbers with those obtained at a corresponding SNE for the same mechanism, but without any mediators involved in the auctions. Such calculations allow us to determine the value of the additional capacity. Our results show that the revenue of the auctioneer, as well as the social value (i.e. efficiency), always increase when mediators are involved; moreover even the payoffs of all the bidders will increase if the mediator has a high enough fitness. Thus, our analysis indicates that there are significant opportunities for diversification in the internet economy and we should expect it to continue to develop richer structure, with room for different types of agents and mechanisms to coexist.

Adaptive online calibration in time stretched ADC arrays

It has recently been shown that photonics can be a powerful tool for manipulating the timescale of electrical signals. Stretching the signal prior to digitization has been proposed as a method to increase the effective sampling rate and the input bandwidth of the ADC, and to effect a reduction in the sampling-jitter noise. Sampling rates greater than 100Gsample/s have been demonstrated with this technique. This paper analyzes the performance of Time Stretch ADC (TSADC) arrays and proposes a novel adaptive calibration technique for mitigating the interchannel mismatch errors. The technique exploits the fact that each channel in the TSADC array is sampled at or above Nyquist rate, a key feature not shared by the conventional sample-interleaved architecture.

Random walks in a dynamic small-world space: robust routing in large-scale sensor networks

The task of moving data (i.e., the routing problem) in large-scale sensor networks has to contend with several obstacles, including severe power constraints at each node and temporary, but random, failures of nodes, rendering routing schemes designed for traditional communication networks ineffective. We consider the open problem of finding optimum routes between any fixed source-destination pair in a large-scale network, such that the communication load (i.e., the required power) is distributed among all the nodes, the overall latency is minimized, and the algorithm is decentralized and robust. A recent work addressed this problem in the context of a grid topology and showed how to obtain load-balanced routing, but transmissions are restricted to be among near-neighbors and the overall latency grows linearly with the number of nodes. We show how one can route messages between source and destination nodes along random small-world topologies using a decentralized algorithm. Specifically, nodes make connections independently (based only on the source and destination information in the packets), according to a distribution that guarantees an average latency of O(log/sup 2/(N)), while preventing hotspot regions by providing an almost uniform distribution of traffic load over all nodes. Surprisingly, the randomized nature of the network structure keeps the average per-node power consumption almost the same as in the case of a grid topology (i.e., local transmissions), while providing an exponential reduction in latency, resulting in a highly fault-tolerant and stable design capable of working in very dynamic environments.

Low latency wireless ad hoc networking: power and bandwidth challenges and a solution

This paper is concerned with the scaling of the number of relay nodes (i.e., hops) individual messages have to transit through in a large-scale wireless ad hoc network (WANET); we call this hop-count as network latency (NL). A large network latency affects all aspects of data communication in a WANET, including an increase in delay, packet loss, and the power needed to process and store messages in nodes lying on the relay path. We consider network management and data routing challenges in WANETs with scalable network latency, e.g., when NL increases only polylogarithmically in the network size. On the physical side, reducing network latency imposes a significantly higher power and bandwidth demand on nodes, and are captured in a set of new bounds derived in this paper. On the protocol front, designing distributed routing protocols that can guarantee the delivery of data packets within a scalable number of hops is a challenging task. To solve this, we introduce multi-resolution randomized hierarchy (MRRH), a novel power and bandwidth efficient WANET protocol with scalable network latency. MRRH uses a randomized algorithm for building and maintaining a random hierarchical network topology, which together with the proposed routing algorithm, can guarantee efficient delivery of data packets in the wireless network. For a network of size N, MRRH can provide an average latency of only O(log3 N). The power consumption and bandwidth requirements of MRRH are shown to be nearly optimal for the latency it provides. Therefore, MRRH is a provably efficient candidate for truly large-scale wireless ad hoc networking.

Diversification in the internet economy: the role of for-profit mediators

We investigate market forces that would lead to the emergence of new classes of players in the sponsored search advertising market. We report a multi-fold diversification triggered by an inherent feature of the sponsored search market, namely, capacity constraints, arising from the fact that there is a limit on the number of available advertisement slots, especially for the popular keywords. As a result, a significant pool of interested advertisers are left out. We present a comparative study of two scenarios motivated by capacity constraints - one where the additional capacity is provided by for-profit agents (or, mediators), who compete for slots in the original auction, draw traffic, and run their own sub-auctions, and the other, where the additional capacity is provided by the auctioneer herself, by essentially acting as a mediator and running a single combined auction. The quality of the additional capacity is measured by its fitness factor. We observe that the single combined-auction model seems inferior to the mediator-based model and market becomes more capacity efficient in the latter. For instance, the revenue of the auctioneer always increases when mediators are involved, unlike the auctioneer based scenario where often there is a tradeoff between the revenue and the capacity. Further, the social value (i.e. efficiency) always increases when mediators are involved. Thus, our analysis indicates that there are significant opportunities for diversification in the internet economy and we should expect it to continue to develop richer structure, with room for different types of market entities and mechanisms to coexist.

Distributed resource sharing in low-latency wireless ad hoc networks

With the growing abundance of portable wireless communication devices, a challenging question that arises is whether one can efficiently harness the collective communication and computation power of these devices. In this paper, we investigate this question by studying a streaming application. Consider a network of N wireless nodes, each of power P, in which one or more nodes are interested in receiving a data stream from a fixed server node S. We ask whether distributed communication mechanisms exist to route media packets from S to the arbitrary but fixed receiver, such that 1) the average communication delay L is short, 2) the load is balanced, i.e., all nodes in the ensemble spend roughly the same amount of average power, and, more importantly, 3) power resources of all nodes are optimally shared, i.e., the lifetime of the network is comparable to an optimally designed network with L nodes whose total power is N ? P. We develop a theoretical framework for incorporation of random long range routes into wireless ad hoc networking protocols that can achieve such performance. Surprisingly, we show that wireless ad hoc routing algorithms, based on this framework, exist that can deliver this performance. The proposed solution is a randomized network structuring and packet routing framework whose communication latency is only L = O(log2 N) hops, on average, compared to O(?(N)) in nearest neighbor communications while distributing the power requirement almost equally over all nodes. Interestingly, all network formation and routing algorithms are completely decentralized, and the packets arriving at a node are routed randomly and independently, based only on the source and destination locations. The distributed nature of the algorithm allows it to be implemented within standard wireless ad hoc communication protocols and makes the proposed framework a compelling candidate for harnessing collective network resources in a truly large-scale wireless ad hoc networking environment.