Gnanambikai Krishnakumar

h-index3
2papers
30citations

2 Papers

2.3ITJan 23, 2025Code
Minimizing Queue Length Regret for Arbitrarily Varying Channels

G Krishnakumar, Abhishek Sinha

We consider an online channel scheduling problem for a single transmitter-receiver pair equipped with $N$ arbitrarily varying wireless channels. The transmission rates of the channels might be non-stationary and could be controlled by an oblivious adversary. At every slot, incoming data arrives at an infinite-capacity data queue located at the transmitter. A scheduler, which is oblivious to the current channel rates, selects one of the $N$ channels for transmission. At the end of the slot, the scheduler only gets to know the transmission rate of the selected channel. The objective is to minimize the queue length regret, defined as the difference between the queue length at some time $T$ achieved by an online policy and the queue length obtained by always transmitting over the single best channel in hindsight. We propose a weakly adaptive Multi-Armed Bandit (MAB) algorithm for minimizing the queue length regret in this setup. Unlike previous works, we do not make any stability assumptions about the queue or the arrival process. Hence, our result holds even when the queueing process is unstable. Our main observation is that the queue length regret can be upper bounded by the regret of a MAB policy that competes against the best channel in hindsight uniformly over all sub-intervals of $[T]$. As a technical contribution of independent interest, we then propose a weakly adaptive adversarial MAB policy which achieves $\tilde{O}(\sqrt{N}T^{\frac{3}{4}})$ regret with high probability, implying the same bound for queue length regret.

2.5CRFeb 23, 2017
GANDALF: A fine-grained hardware-software co-design for preventing memory attacks

Gnanambikai Krishnakumar, Patanjali SLPSK, Prasanna Karthik Vairam et al.

Reading or writing outside the bounds of a buffer is a serious security vulnerability that has been exploited in numerous occasions. These attacks can be prevented by ensuring that every buffer is only accessed within its specified bounds. In this paper we present Gandalf, a compiler-assisted hardware extension for the OpenRISC processor that thwarts all forms of memory based attacks including buffer overflows and over-reads.The feature associates lightweight base and bound capabilities to all pointer variables, which are checked at run time by the hardware. Gandalf is transparent to the user and does not require significant OS modifications. Moreover, it achieves locality, thus resulting in small performance penalties.